{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Подключение необходимых библиотек\n",
    "import random\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import timeit\n",
    "import string\n",
    "import pprint\n",
    "import pandas as pd\n",
    "from random import shuffle\n",
    "\n",
    "sample_str = string.ascii_letters  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1)   Реализуйте   алгоритм   последовательного   поиска.   Определите\n",
    "вычислительную   сложность   алгоритма   в   среднем   на   задаче   поиска   числа   в\n",
    "массиве, буквы в строке."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Массив :   [4, 15, 0, 6, 7, 7, 6, 14, 2, 17, 3, 1, 15, 5, 16, 14, 0, 13, 10, 3]\n",
      "Ключ к массиву : 7\n",
      "Индекс найденого элемента:  4\n",
      "Строка :   lHZfthWvMTZNakugytzq\n",
      "Ключ к строке : u\n",
      "Индекс найденого элемента:  14\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "def linear_Search(A,  key):                                               # Алгоритм линейного поиска \n",
    "  for i in range(0, len(A)): \n",
    "    if (A[i] == key): \n",
    "        return i \n",
    "  return -1  \n",
    "\n",
    " \n",
    "\n",
    "A = [random.randint(0,19 ) for i in range(20)]                             # создание массива случайных чисел\n",
    "key1 = 7 \n",
    "print(\"Массив :  \",A)\n",
    "print(\"Ключ к массиву :\",key1)\n",
    "\n",
    "res1 = linear_Search(A,  key1)                                             # поиск числа в массиве\n",
    "if(res1 == -1): \n",
    "    print(\"Элемент не найден\") \n",
    "else: \n",
    "    print(\"Индекс найденого элемента: \", res1) \n",
    "\n",
    "B = ''.join(random.choice(sample_str) for _ in range(20))                  # создание строки случайных символов\n",
    "key11 = 'u' \n",
    "print(\"Строка :  \",B)\n",
    "print(\"Ключ к строке :\",key11)\n",
    "\n",
    "res2 = linear_Search(B,  key11)                                            # поиск символа в строке\n",
    "if(res2 == -1): \n",
    "    print(\"Элемент не найден\") \n",
    "else: \n",
    "    print(\"Индекс найденого элемента: \", res2)   \n",
    "\n",
    "\n",
    "t1=np.zeros(50)                                                             # Создание массива для результатов обработки времени\n",
    "t11=np.zeros(50)\n",
    "n1=np.arange(1,51,1)                                                        # Создание массива длин вектора \n",
    "n=1\n",
    "while n<51:\n",
    "    A = [random.randint(0, 9) for i in range(n)]                             # Создание вектора размера n \n",
    "    t1[n-1] = timeit.timeit('linear_Search(A,key1)', globals=globals())     # Расчет времени выполнения алгоритма \n",
    "    B = ''.join(random.choice(sample_str) for _ in range(n) )                # Создание вектора размера n \n",
    "    t11[n-1] = timeit.timeit('linear_Search(B,key11)', globals=globals())   # Расчет времени выполнения алгоритма \n",
    "    n+=1\n",
    "\n",
    "fig, ax = plt.subplots(figsize = [12,6],dpi = 100)                          # Построение графиков \n",
    "plt.grid(visible=True)\n",
    "ax.set_xlabel(\"Длина массива\") \n",
    "ax.set_ylabel(\"Время выполнения сек\") \n",
    "ax.set_title('Оценка времени выполнения алгоритма последовательного поиска ') \n",
    "ax.plot(n1,t1,n1,t11)\n",
    "ax.legend(labels = (\"поиск числав в массиве\",\"Поиск символа в строке\"), loc=\"upper left\");\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2) Повторите п. 1 для алгоритма бинарного поиска."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Массив :   [3, 6, 7, 2, 1, 0, 17, 17, 17, 14, 5, 12, 8, 9, 18, 17, 16, 16, 19, 17]\n",
      "Ключ к массиву : 3\n",
      "Индекс найденого элемента:  0\n",
      "Строка :   bpIhEoxNdmOzcRfyxWwX\n",
      "Ключ к строке : z\n",
      "Индекс найденого элемента:  11\n"
     ]
    },
    {
     "data": {
      "image/png": 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jnNlNwX1WV5Cz5vQSXG3ylGznDMe15phlc812kIc1Pt5HT64yE73HXJ27FjQPm3wcM6/m4/1xN6NOye+Axo3AfS1ufu3f8ojTFwuk5krKEnDJfu5zVMTdNPuuAMfN+4TWJhlj5gD9jDF3Z3aLMG4QyitwN09W5trtciDrd8q4wfIa4GqsswvF3fQanytZKRJvsv8OrsXOu9bafT6Sf4v7Ls39fXQtuZp352ES7ibkFbgbM5ku9+6f+2ZRYX5vC3LNFfha8DrbGFMzs8m79+/JANzvQe4bYMty/e7naF3i5zXhUyCPVQBTgPuMMSdba//Ktv5KfHebOhXXfeCC7ElzLj8AQ4wxza21K45x/ge8TdzfMW7k+g+NG0wx8+aAxf1Nyv53PxoYUpAXJyJFpyRdRHyy1v5ujLkDN/r5b8ZNg7UBqI9rtnkacIe3j2duTXP9M9XA+7OWMaaWtXYrrjbmclyN6Cu4O/tpuJqAs4BvrLVfBeClvIxL+j4xbiTzfbhRdffiahAe8Z73ctxURoVxkvef0QjgJKAnRxLv7Pp5+5lO5sjo7gtxtWxYa9cZYx4EnjBueqhJ3vhq4v45S7LWPpT7oN4WD31wgzD5+hwyP8d3gJHGTWc0HZfY1wJOx91oeLOQrzvTRbhm9I8cq2AeqhtjOnkfV8PVpFvce5NdJeOmz8us4b4LOIQbzKk2/puMu0HyjHGjXP/OkdHd5+P6oWbepLgPd1OgdxHOl9uDuGtmpjHmf7jRvaNw3Uj6ADf6asVSQDcCr1trc7+XWbzX7nu45HFCIY8/EXddv4EbdKweLlHciqs1zzzHxbjmtBUJTBPy+3Cf21RjzPO47jI34z6bQdkTRa8Oxpj3cOMM1MM1193M0SPLd8a1IrggADHm9gKua8oiXxuttYnGmOnAPcaYXbgBwc7EJWX7jnVwa+1MY8zXuJuRFXFNxDNHd5+De+3ZFfX3NrcCXQvZ7AJ+MW5+98zR3VtwdAuegirsNVFSx8rPS7iE/Dvvd/963IwBNwNvWmtz3wy4HvjWWpvfja4Hcd9P040xT+K+HyvhWqu96GtsFq9rvGXfAy72rvsO9z072vv3oypuoElfrbFEpBgoSReRPFlrXzXGzMUNLPQC7g/1HlzT89OttbPy2DWv9U/iBt4Z6k0wL8Q1ox6C++coHVdb8Svun4ZAvIbMOWYX4UbTHmit3e2tPXgB15QzCdc/dwBHptYqiC+9PzP7Sn6Cj/59uGbED+OmVLK4GvA7rLWZAz5hrX3KGLMU934Mwk1rtA3X5PqtfF7fUiDf2jBr7Q3GmNm4lgI348Yj2YJLSnMPXFQYocBwX4MOFVAf7wIuGVkGXOqjZcXl3sXirr+FQB9r7daiNEn2XhsX4z6bYbhm57twyfn/2SPTr92O+3t5XoBrWbd6b5w8gOu6URfXzWMtR27U+Gs3vgeLA7Ka9I/yniN3N5JjstaONMbUwN0MuBpYg2tVUxfXvSTTf3HJ2s3W2iL/TltrfzXG9MAlmKNw1/JC4EJr7UQfu1yD+34Zg/udmoobBT33OBqhuDElijpYnK+Y95GzibYvg3FNy5/FXWu/427gFLT1wUDcdXwd7v3fjku67rdHT79W1N/bHApxLWSagBt34XHcTd/VuJkuCjumReb5C3tNlMixjnGend5WHU95l3jc+zYCeNHHLmn4Hiwu+zE3e/uSP4JrPVUV1wT+N/IZN8Zau8sYMwx3w/xGa+1b1tpfjDFX47rtfIu7sfUubuyK9wvzWkXEP5nTUoiIFDtjzCgAa+3Q4EZSMowxD+P+Sa1u85/nWEQCyHtjbiTQMXdzbQkeY4zFtfC4JdixiIiUZqpJF5GS5Gs0WxERERER8VKSLiIlxlp7X7BjEBEREREpzdTcXURERERERKSUCAl2ACIiIiIiIiLiKEkXERERERERKSWUpIuIiIiIiIiUEuVu4Djv3LC1cXPRioiIiIiIiJSEOGCLPcbAcOUuSccl6JuCHYSIiIiIiIiUO3WBzfkVKI9J+gGAjRs3Eh8fXywnSEtL46effuLcc88lPDy8WM4hEki6ZqWs0TUrZYmuVylrdM1KWVJWrtfExETq1asHBWjRXR6TdADi4+OLNUmPiYkhPj6+VF8oIpl0zUpZo2tWyhJdr1LW6JqVsuR4vF41cJyIiIiIiIhIKaEkXURERERERKSUUJIuIiIiIiIiUkqU2z7p+bHWkp6eTkZGhl/7p6WlERYWRkpKit/HEClJpe2aDQ8PJzQ0NNhhiIiIiIiUOCXpuaSmprJ161aSk5P9Poa1loSEBDZu3Iibll2kdCtt16wxhrp16xIbGxvsUERERERESpSS9Gw8Hg9r164lNDSU2rVrExER4VfC4vF4OHjwILGxsYSEqEeBlH6l6Zq11rJz5042bdrECSecoBp1ERERESlXlKRnk5qaisfjoV69esTExPh9HI/HQ2pqKlFRUUFPeEQKorRds9WrV2fdunWkpaUpSRcRERGRciX4/42XQqUhSREpz0pDk3sRERERkWBQNioiIiIiIiJSSihJFxERERERESkllKSLiIiIiIiIlBJK0kVERERERERKCSXpIiIiIiIiIqWEkvRjsNaSnJpe6OVQaoZf+2VfrLUFjrN79+4YY45a2rdvn1XG4/Hw6KOPUrduXSIjI2nfvj2TJk3K2r5u3TqMMSxYsCBr3f33348xhpdffjlr3b59+7j++uupWbMmUVFRtG7dmokTJwIwatQoKlWqlFV2w4YN1K9fn/vuuy/f2O+4444845g2bRrGGPbt25dV5oorrsAYw9dff521btOmTQwcOJAqVapQoUIFOnTowJw5c446bu4l87irV6/moosuombNmsTGxtKxY0d+/vnnHLE2bNgwa78KFSrQpUsX/vzzzzxfW2bsxhhCQkKoUaMG11xzDSkpKXnuM3ToUIwxvPjiiznWX3zxxRhjGDVqVNa6e++9l2bNmhETE0Pjxo154IEHSEtLy7HfhAkT6NChA1FRUVSrVo1+/fplbTt8+DAjRoygQYMG1KxZk+bNm/P+++8X+H3P/Z5WqVKFfv36sXv37qx9UlNTGTFiBHXq1KFChQqcdtppTJs2Lc/XLyIiIiJSnmme9GM4lJZBywd/DMq5lz56HjERBf+IrrvuOh599NGs588//3yOJPOVV17hhRde4O233+akk07igw8+4MILL2TJkiWccMIJRx1v06ZNvPLKK0RHR2et83g89O7dmwMHDvDJJ5/QpEkTli5d6nMu6+3bt3POOefQt29fnnrqqQK/jmOZN28e3377bY51Bw8e5Mwzz6ROnTpMmDCBhIQE/vrrLzweT1aZzJseP//8M61atWLmzJlccsklOY7Rp08fHn/8caKiovjwww+54IILWLFiBfXr188q9+ijj3Ldddexd+9ebrvtNv7973/nuBngy4oVK4iLi2Px4sX069ePDh06cNNNN+VZvk6dOrz77rvcddddAGzdupWZM2cSExOTo1xcXByjRo2idu3aLF68mOuuu464uDhGjBgBwHfffUe/fv3473//y8cff0xqairfffdd1v5XXnkls2bN4uWXX6ZJkybs3LmTPXv2FPh9z5T5nq5du5ZLL72UZ599lmeeeQaAYcOGsW7dOsaMGUPt2rX56quv6NWrF4sXL/Z53YmIiIiIlGdK0o8jMTExJCQkZD2PjY3Nsf3555/n3nvvZeDAgQA888wzTJ06lZdffpnXX3/9qOP997//ZcCAATkS/Z9//pk//viDZcuW0axZMwAaN2581L579+7l3HPP5dRTT+W1117LN+7o6GgOHTpU4Nd51113cc899/DAAw9krRs9ejQ7d+5k7ty5VKlSBYCmTZvm2C+zhjkhIYGEhISscpnatWtHu3btsp4//vjjfPXVV0yYMIFbbrkla31cXBwJCQlUqlSJypUr+7xBkVuNGjWoVKkSSUlJREREULly5XzLd+jQgbVr1zJjxgy6devG+++/z8CBA/noo49ylLv//vuzHjds2JDhw4czduzYrCT9iSeeYODAgTzyyCM5XifAypUrGTduHJMnT6ZHjx4kJibStm1bQkJ8N7Dx9b5nqlq1ata1Fx0dnfX6Vq9ezWeffcamTZuoXbs2AHfffTeTJk1i5MiRPPnkk/m+DyIiIiIi5Y2S9GOIDg9l6aPnFWofj8fDgcQDxMXH5ZnwFPTcgZKYmMiWLVvo2rVrjvVdu3Zl4cKFR5X/66+/+Oqrr1ixYkWOJH3BggXUrVs3K0H3JT09nT59+rBo0SLuuuuuY74HrVq14ssvv2Tnzp1Ur14937Jff/01a9asYfjw4TmSxQULFnDSSScdlXhnl5iYCECFChV8bk9KSuKRRx5h4sSJbNmyhfT0dA4dOsSGDRtylLv33nu5//77OXToEPXq1eOnn37KN2aAunXruq4TyckMHjyYAQMGHHOf6667jnfeeYeuXbvy/vvvM2HChKOS9C+++IKXX36ZVatWcfDgQdLT04mPj8/avmDBAq677jqfx1+wYAGhoaGceeaZx4wlr/c9U5cuXQgJCSEpKYnu3btz5513Au46stYedb0cPnyYqlWrHvO8IiIiInKcSk+FyQ9AlSZw2vXBjqZUUZ/0YzDGEBMRVuglOiLUr/2yL8aYYnk92VlrfZ5n+PDh3H333dSqVSvH+uxN3/OSlJREdHQ0b7/9NnfeeSdbt27Nt/zdd99NfHw8CQkJxMbG0qpVK5/l0tLSGDFiBE888cRRcRQkri1bthASEpKjtUF299xzD+PHj+eJJ55gxowZLFiwgDZt2pCamnpUuQULFjB//nzOPfdcLrzwQg4fPpzvuWfMmMHChQuZMmUK8+bNy9EtIS9Dhgzh+++/Z8yYMSQkJNCmTZsc22fPns3AgQPp3bs3EydOZP78+fz3v//NEW9+70tB3jPI/33PNHbsWBYsWMDMmTNJTU3lxhtvBNwNq9DQUObNm8eCBQuylmXLlvHKK68U6PwiIiIichya9hTMeQt+uAeWfx/saEoVJenlRHx8PLVr1+a3337LsX7mzJmceOKJOdZNmDCBlStXcvfddx91nLZt27Jp0yZWrlyZ57liYmKYMGEC119/PV27duX66/O/M5aQkMCCBQvYsGEDCxYs4Pvvff+Svvnmm8TGxjJkyBCfcS1YsCDP/tQAc+fOpUWLFkRFRfncPmPGDIYOHcq//vUv2rRpQ0JCAuvWrTuqXLVq1WjatClt27blwQcfZMWKFfz999/5vsZGjRrRtGlTevTowRVXXMEXX3yRb3mAihUrcuGFF3LjjTf6rA3//fffadCgAf/973/p0KEDJ5xwAuvXr89Rpm3btkyZMsXn8du0aYPH4+HXX3/NN4783vdM9erVo2nTpnTu3Jmbbrop6/WddNJJZGRksGPHDpo2bZpjyetmiYiIiIgc5zbMgd9fPvL8m5th/+aghVPaqLl7OXLPPffw0EMP0aRJE9q3b8/IkSNZsGABn376aY5yzz77LK+++upRg5QBnHnmmZxxxhlccsklvPjiizRt2pTly5djjKFXr14AhIeHZ/WHf+edd2jVqhUfffQRV155Zb7x1alTB4CwMN+X5bPPPsuECRN81vwPGjSIJ598kosvvpinnnqKWrVqMX/+fGrXrs0pp5zC2LFjefHFF/OtwW7atClffvklF1xwAcYYHnjggRwDz2U6cOAA27Zt49ChQ7z22mtERUXRsGHDfF/bjh07SElJYdOmTXz++ee0aNEi3/KZ/vOf/9C8eXOfzeObNm3Khg0bGDNmDB07duS7777jq6++ylHmoYce4uyzz6ZJkyYMHDiQ9PR0fvjhB0aMGEHDhg256qqruPrqq7MGjtu9eze7du3isssuyzpGfu97pt27d7Nt2zZ27drFqFGjsl5fs2bNuPzyy7nyyit54YUXOOmkk9i1axe//PILbdq0oU+fPgV6H0RERETkOHH4IHx1PVgPtO4Pe1bDlvkw/lq46lsIVYqqmvRy5LbbbmP48OEMHz6cNm3aMGnSJCZMmHDUCNtNmzblqquuyvM448ePp2PHjgwaNIiWLVsyYsQIMjIyfJatVasWr7zyCrfffjtbtmwpUvxnnXUWPXr08LktIiKCn376iRo1atCnTx/atGnD008/TWhoKIsXL+bhhx/mgQceyOor7ctLL71E5cqV6dKlCxdccAHnnXceJ5988lHlHnzwQWrVqkXLli2ZNm0aX3755TH7Vzdv3pxatWrRq1cvmjdvfszB9LLv95///MdnP/qLLrqIO++8k1tuuYX27dszc+bMo/qLd+/enc8//5wJEybQvn17evTokWMk+jfffJP+/ftzyy23cOqpp3LDDTeQlJSU4xj5ve+ZzjnnHGrVqsXpp59OWFhYjhs/I0eO5Morr2T48OE0b96cCy+8kDlz5lCvXr0CvQciIiIichz56b+wdx3E14W+L0L/DyAiDjbMhOnPBTu6UsEUZi7u44ExJh7Yv3///hwDbAGkpKSwdu1aGjVqlGeT6ILweDwkJiYSHx9fpIHjREpKabtmA/W7KMevtLQ0vv/+e/r06UN4eHiwwxHJl65XKWt0zUqxWfkjjPa22LxyAjT2DmC8+AsYfw2YEFeb3vD0Ah+yrFyviYmJVKxYEaCitTYxv7LB/29cREREREREjm9Ju+Eb77TGnW4+kqADtOkP7a9wTeDHX+fKlmNK0kVERERERKT4WAsT74CkHVCtOZz94NFl+jwLVU+AA1vgm3+7fcqpoCbpxpibjDGLjDGJ3mWWMab3MfY50xgzzxiTYoxZY4y5saTiFRERERERkUJaNBaWTYCQMOj3DoT7mNY3ogJcOhJCI2HlDzDn7ZKPs5QIdk36JuA/QAfv8gvwjTHG50TZxphGwPfADOAk4Engf8aYS0omXBERERERESmwfRvh+3vc4zP/A7Xb5102oQ2c94R7PPkB2Lqw2MMrjYI6vr219ttcq/5rjLkJ6AQs8bHLjcAGa+0d3ufLjDEdgLuB8b7OYYyJBCKzrYoDN8BAWlpajrJpaWlYa/F4PD6n3iqozMH4Mo8lUtqVtmvW4/FgrSUtLY3Q0NBghyOlUOb3d+7vcZHSSNerlDW6ZouBtYT8+T62QjXsiRdBPlPbHlesh9CvbiTkcCKeOh3I6HQLHOu6an8Voat+IWTl99jPh5J+9RSIjMuzeFm5XgsTX6kZ3d0YEwpcCnwInGStXeqjzHRgvrX29mzr/gWMA2KstUe9cmPMw8BDudePHj36qHnAw8LCSEhIoF69ekRERBTxFYmIv1JTU9m4cSPbtm0jPT092OGIiIiIFEnlpNWcsfIRAHbFNmdR3as4EF03yFEVv8Y7JtFm82jSQyKY1vxxkqISCrRfePpBui+/n5i0PWyo0pX5DW4o5kiLX3JyMoMHD4YCjO4e9CTdGNMGmAVEAQeBwdba7/MouxIYZa19Mtu6LsDvQG1r7VYf+/iqSd+0a9cun1Owbdy4kYYNGxZp2idrLQcOHCAuLg5TXu6SSZlW2q7ZlJQU1q1bR7169TQFm/iUlpbG5MmT6dmzZ6mebkUEdL1K2aNrNvBCZv2P0F8ezXpuQ8LwnHYTntOHQ0RsECMrRjtXEPZ+D0zGYTJ6PYvnlKsLtbvZMIvQTy7CWA/pF76BbXOZz3Jl5XpNTEykWrVqUIAkPajN3b1WAO2BSsAlwIfGmDN91aR75b6rYPJY71Zaexg4nFXYm4CEh4cf9SFmZGRgjCEkJKRIc0VnNhfOPJZIaVfartmQkBCMMT5/T0Wy0zUiZYmuVylrdM0G0Ka57menm2HfBszyiYTOepXQJV9Cr6fhxAuOrybw6anw7c2QcRiankPoadcTWtjX1+QM6H4fTH2CsB/ugfqnQbWmeRYv7ddrYWIL+n/j1tpUa+0qa+2f1tr7gIXA7XkU3wbkbiNRA0gHyvdkeiIiIiIiUvp4PLBhlnvcuj8M/BQGjYVK9SFxM4wbAp9eCnvWBDfOQJr+rBv0LboyXPia/zcgug2Hht0gLQm+GAbph4+9z3Eg6Em6D4aczdOzmwX0zLXuXOBPX/3RRUREREREgmrXCkjZB+ExUKutW9e8F9w8B864B0IjYNVkeL0TTHsG0lKCGm6RbZwLM15wj89/EeJr+X+skFA3ZVt0Fdi2CH5+OCAhlnbBnif9SWNMN2NMQ2NMG2PME0B34FPv9qeMMR9l2+UtoIEx5kVjzInGmKuBa4DnSzz4Umbo0KEYY/Jc9u3bF+wQRURERETKn/Uz3c+6HSA0W5PniBjocT/cNAsad3dNw6c9CW92hlU/ByXUIktNgq+uB+uBNpdC635FP2Z8bfjXW+7x7DdgxQ9FP2YpF+ya9JrAx7h+6VOA04Be1trJ3u21gPqZha21a4E+uER+AfAAcJu11uf0a+VNr1692Lp1a45l/Hi9NSIiIiIiQbNhtvtZv7Pv7dWawpCvof9IiE1wzd4/uQTGXQn7N5dYmAHx0wMu/rja0Oe5wB232XmuPz/A1zdD4pbAHbsUCmqSbq29xlrb0Fobaa2tYa09J1uCjrV2qLW2e659frXWnuzdp5G19q1iDtLdESrskpbs337Zl0KOvB8ZGUlCQkKOpUqVKkeVGz9+PK1atSIyMpKGDRvywgsv5NjesGFDXn755aznU6ZMwRjDxRdfnLXO4/HwzDPP0LRpUyIjI6lfvz5PPPEEAOvWrcMYw4IFCwA3ndZ5553HWWedRUpK3s13lixZwvnnn098fDxxcXF069aN1atXA66lQPbz7969m0qVKlGpUqWsdQ8//DDGGG677bYcx73jjjswxvDwww9nrcveyiA+Pp6ePXtmnQvg8OHD3HbbbdSoUYOoqChOP/105s6de1TMDRs2PKrVwtdffw24gQivueYaGjVqRHR0NM2bN+eVV17J8/UDTJs2Les4ISEh1KhRg2uuuSbf9w3ggw8+yPpMa9WqxS233JJnfJnLqFGjst6LN998k/79+1OhQgUaNWrE559/nuP4ixcvpkePHkRHR1O1alWuv/56Dh48mLU99+fz448/Ehsby8SJE7PWbd68mQEDBlC5cmWqVq3KRRddxLp16/J9XSIiIiJlXmZ/9LySdHB9tlv3g1vmQqd/gwmFpd/Aax1h5quQUQZ69v7zM/z5vnt88RuuP3ognfMw1GoHh/bA+OvAkxHY45cipWF099ItLRmerF2oXUJwQ9UX2f9tgYgKgThSlnnz5nHZZZfx8MMPM2DAAGbOnMnNN99M1apVGTp06FHlPR4Pw4cPJzY259QQ9913H++++y4vvfQSp59+Olu3bmX58uVH7Z+RkcHAgQPZu3cvU6ZMyXM6rc2bN3PGGWfQvXt3fvnlF+Lj4/n999/znCP7kUceISMjg9DQ0Bzra9asyWeffcYzzzxDdHQ0KSkpjB49mpo1ax51jJEjR9KrVy+2bdvGVVddxf/93/8xduxYAEaMGMH48eP58MMPadCgAc8++yznnXceq1atynHjw1rLo48+ynXXXQdArVpH+tx4PB7q1q3LuHHjqFatGjNnzuT666+nVq1aXHaZ7ykkMq1YsYK4uDgWL15Mv3796NChAzfddJPPsm+++SZ33XUXTz/9NL1792b//v38/vvvAMydO5eMDPcF1rFjR+6++24GDBgAQMWKFbOO8dBDD/Hggw/y2muv8emnnzJo0CBat27NiSeeSHJyMr169aJTp07MnTuXHTt2cO2113LLLbdkJfrZ/fbbb/Tv3593332Xvn37Am5eyLPOOotu3boxffp0wsLCePzxx+nVqxeLFi0iIiIi3/dDREREpEzatxH2b3RJd92Oxy4fFQ+9noT2g+C74bBxDvx0PywY7fp3N8gn0Q+m5D3wzb/d41NvgCZnBf4cYZGutcHbZ8D632D689D93sCfpxRQkl7OvPjii5x99tk88MADADRr1oylS5fy3HPP+UzSP/zwQ1JSUrjooouyak4PHDjAK6+8wmuvvcZVV10FQJMmTTj99NNz7Gut5eqrr2blypVMnz6duLi4PON6/fXXqVixImPGjMmanqBZs2Y+y65cuZIPPviAu+66i//97385tiUkJFC/fn2++OILhgwZwhdffEGnTp3YsGHDUcepVKkSCQkJREdHExcXR+XK7m5fUlISb775JqNGjaJ3794AvPvuu0yePJn333+fe+65J+sYaWlpVKlShYSE3JMOuGkWHnnkkaznjRo1YubMmYwbN+6YSXqNGjWoVKkSSUlJREREZMXmy+OPP87w4cO5/fYjkyJ07Oj+CFSvXj1rXWhoKBUrVvQZa//+/bnyyiuJj4/nscceY/Lkybz66qu88cYbfPrppxw6dIiPPvqIChXcTaPXXnuNCy64gGeeeSbHDZD58+fTt29fnn/+eQYNGpS1fsyYMYSEhPDee+9lTYM4cuRIKlWqxLRp0zj33HPzfT9EREREyqTMpu612kJkIeZDT2gDwybBgk9h8oOwYymM7AXtBkPPRyC2RvHE6w9r4bu74OA2qHqCq/EuLlWbuJsVX10Pvz4NjbpB7QLc/ChjlKQfS3iMq9EuBI/HQ+KBA8THxRVtzunwGP/3zcOyZcu46KKLcqzr2rUrL7/88lE108nJydx///289dZbOfq2L1u2jMOHD3P22Wfne6577rmHKVOmMHToUJ/N7rNbsGAB3bp1K9D8gSNGjOCGG26gcePGPrdff/31PPPMMwwZMoR33nmHESNGcP/99x9VbtCgQYSGhpKcnEybNm14/PHHAVi9ejVpaWl07do1q2x4eDinnnoqy5Yty3GMxMTErMTVl7feeov33nuP9evXc+jQIVJTU2nfvv0xX2PdunWx1pKcnMzgwYOzar9z27FjB1u2bDnmZ3EsnTp1yvG8c+fOWd0Vli1bRrt27XK8zq5du+LxeFixYkVWkr527VrOO+88UlJSOOusnHdP582bx6pVq466UZOSkpKjm4GIiIjIcaUgTd3zEhICJw+BFufDlEdg3ihYONot0ZUhvi5UrAPxdaBiXbfE13Hr4mpDWAm1VFz8BSz5yrUW6Pe2GxCvOLUbAGumwsLPYPy1cM3U4j1fEChJPxZjCt/k3OOB8Ay3X1GS9GJgrc2qycy+zpfnnnuO5s2bc8EFF+RI0qOjowt0rmXLlvHDDz/Qr18/BgwYQK9evfIsW9Bj/vrrr8yYMYORI0fyzTff+CzTu3dvbr75Zr766ivWrl1L7969fSbpL730Eueccw6JiYk8+uijXHrppUydOjXr/fD1PmVfl5iYSFJSErVr++4OMW7cOO68805eeOEFOnfuTFxcHM899xxz5sw55uucMWMGcXFxbNiwgZtvvplHH32Uhx566KhyBX3f/JH5Wn1dM7nLACxatIj//Oc/bN++nWHDhjFjxoysm1Qej4dTTjmFTz/99KhjZK/tFxERETmuFCVJzxRTBS54BdpfAT/cA1vmw6G9btm+OI+djKttz0zafSX0sQlFz1X2b4bvh7vHZ46AOqcU7XgF1ed52PgH7FlN6MTboMKgY+9ThihJL2datmzJb7/9lmPdzJkzadasWY5a9K1bt/Lmm28ybdq0o45xwgknEB0dzZQpU7j22mvzPNfHH39Mjx49eOyxx7j22mtZsmRJjn7Q2bVt25YPP/yQtLS0PGvTrbUMHz6cBx54IN/m36GhoVxzzTVcddVV3HHHHUf1W8+UkJBA06ZNAbj77rvp1q0bu3fvpmnTpkRERPDbb78xePBgwDVr//PPP7njjjuy9p87dy7GmDxrxmfMmEGXLl24+eabs9YVtNa4UaNGVKpUiaZNm3LFFVcwduxYn0l6XFwcDRs2ZMqUKUfVXhfGnDlzcgz8Nnv2bE466STAXTMffvghSUlJWbXpv//+OyEhITm6JHTr1o2nnnqK/fv307p1a1566SWGD3df2ieffDJjx46lRo0axMfH+x2niIiISJlxaK9rpg5Qv1P+ZQuiXke4bqqbc33/ZkjcDPs3eX9mf77FTed2cLtbtvzl+3hhUVCpAVRpBJUbQuVG3seNoFJ9CPc9llQWjwe+uRlS9kPtk6Hb8KK/xoKKjIVLR8J75xDyzyQa1a0OnF9y5y9mStLLmeHDh9OxY0cee+wxBgwYwKxZs3jttdd44403cpR7/fXXueSSSzj55JOPOkZUVBT33nsvI0aMICIigq5du7Jz506WLFnCNddck1Uus4n7nXfeyZdffsmdd97JBx984DOuW265hVdffZWBAwdy3333UbFiRWbPns2pp55K8+bNATfKfK1atXIkvXm54YYbiIyM5Morr8yzzL59+9i2bRuJiYm88cYb1KhRgypVqmCM4aabbuKee+6hSpUq1K9fn2effZbk5OSs1zd16lT+/e9/c/7551Ojhu8+QU2bNuWjjz7ixx9/pFGjRnz88cfMnTuXRo0aHTP+HTt2kJKSwqZNm/j8889p0aJFnmUffvhhbrzxRmrUqEHv3r05cOAAv//+O7feeusxz5Ppiy++oFWrVpxzzjl89tln/PHHH7z/vhud8/LLL+ehhx7iqquu4uGHH2bnzp3ceuutDBkyJEd/9MzPu2LFirzzzjtccskl9O3bl+bNm3P55Zfz3HPPcdFFF/Hoo49St25dNmzYwJdffsk999xD3bp1CxyriIiISJmwwdt6smrTwPUhN8Y1dY+uDAmtfZexFpJ2QeKmvJP5xC2QngK7Vrjl6BO5+ckrN4IqDY9O4qMrw9x3Yc00CIuGfu/knAO+JNRqBz0fg0n30mrzZ3i2XQ31js5dyiIl6eXMySefzLhx43jwwQd57LHHqFWrFo8++uhRg8Z5PJ6sKdV8eeCBBwgLC+PBBx9ky5Yt1KpVixtvvNFn2ZCQEEaOHEn79u3p378/ffr0OapM1apV+eWXX7jnnns488wzCQ0NpX379jn6hSclJfH0008XaCTwhIQE/vOf/+RbZtiwYQDExsbSvn17JkyYkNV8++mnn8bj8TBkyBAOHDhAhw4d+PHHH7Nq8K+++mrOOeccnnsu7/kfb7zxRhYsWMCAAQMwxjBo0CBuvvlmfvjhh2PGn3ljomrVqvTo0YNXX301z7JXXXUVKSkpvPTSS9x9991Uq1aN/v37H/Mc2T388MOMHz+eu+++m4SEBD799FNatmwJQExMDD/++CO33347HTt2JCYmhksuuYQXX3wxz+P17t2bQYMGMWzYMH777TdiYmKYPn069957L/369ePAgQPUqVOHs88+WzXrIiIicnzKauoegFr0wjAGYqu7pfZJvstkpLtR5/euhb3rYM9a93jPOvcz9aA3md/sRlLPLbKimwULoOejUO2E4no1+TvtBjyrfyF5wyKiQny3ni2LTF79kY9Xxph4YP/+/fuPSg5SUlJYu3YtjRo1ynOqsILweDwkJiYSHx9ftIHjREqAMYbx48fTo0ePUnPNBup3UY5faWlpfP/99/Tp06dAA06KBJOuVylrdM0GyPvnuinULnoDTro82NEUnLWQvDtb4r42ZzJ/cNuRsk16wOXjgzoOV1riTn78eSrnXfCvUn29JiYmZnb9rWitTcyvrGrSRUREREREAintEGz29gUv6Zr0ojIGKlRzSz0f05ulJruE/eA2qHda8AfKjq5ERmhkcGMIMCXpIiIiIiIigbRlPnjSILYmVPE9bXCZFREDNVu6RYqFknSRcs5am9VFQ0REREQCYP1M97N+J1czLVIIwe98KiIiIiIicjzZMNv9rN8luHFImaQk3YfyNpieSGmj30EREREpszwZbsA4KHv90aVUUJKeTeZogMnJyUGORKR8S01NBSA09PiZSkNERETKiR1L4XAiRMRBzTzmMhfJh/qkZxMaGkqlSpXYsWMH4OaHNn70IfF4PKSmppKSklIqprMSOZbSdM16PB527txJTEwMYWH6ihIREZEyZr13fvR6HSFU/8tI4emqySUhIQEgK1H3h7WWQ4cOER0d7VeSL1LSSts1GxISQv369UtFLCIiIiKFssGbpKs/uvhJSXouxhhq1apFjRo1SEtL8+sYaWlpTJ8+nTPOOCOrCb1IaVbartmIiIig1+iLiIiIFJq12ZJ09UcX/yhJz0NoaKjf/WFDQ0NJT08nKiqqVCQ8Iseia1ZEREQkAPathwNbISQc6pwS7GikjFJVlYiIiIiISCBk9kev3R4iYoIaipRdStJFREREREQCIaupe+fgxiFlmpJ0ERERERGRQFCSLgGgJF1ERERERKSoknbBrpXusQaNkyJQki4iIiIiIlJUG2a7n9VbQEyV4MYiZZqSdBERERERkaJSU3cJECXpIiIiIiIiRaUkXQJESbqIiIiIiEhRpCbB1oXucQMl6VI0StJFRERERESKYtOf4EmH+DpQsV6wo5EyTkm6iIiIiIhIUWQOGle/ExgT3FikzFOSLiIiIiIiUhQbZrqf6o8uAaAkXUREREREjk+pSbBtcfGeIyMdNs51j5WkSwAoSRcRERERkePPzpXw1ulumf9J8Z1n2yJIS4LIilCjZfGdR8oNJekiIiIiInJ8WT0V3jsH9qxxz6c9DempxXOurP7op0GI0ispOl1FIiIiIiJy/Jj7PnxyCRzeD3VPhdiasH8jLBxdPOdTf3QJMCXpIiIiIiJS9mWkww/3wnd3gc2ANpfBVd9C1zvc9hkvQEZaYM9pbbaadCXpEhhK0kVEREREpGxL2Q+fDYA5b7nnPR6Afu9AeBR0GAYVasC+DbDws8Ced/dqSNoJoZFQ5+TAHlvKLSXpIiIiIiJSdu1dB++fC6t+hrBouPRDOOPuI/OVh0dD19vd4+nPB7Y2fcMs97POyRAWGbjjSrmmJF1ERERERMqm9bPg3R6wcznE1YJh30Ori48u1+FqqFAd9q2HRWMDd/7MJF1N3SWAlKSLiIiIiEjZs+Az+OhCSN4NtdrBdb/k3eQ8Iga63OYeT3/e9V8PBCXpUgyUpIuIiIiISNnh8cDPD8PXN0JGKpx4AQz7AeJr579fx2sgphrsXQuLxxU9jgPbvVO8Gah3atGPJ+KlJF1ERERERMqG1CQYNwR+e8k97zYcLv0IIioce9+ICtDlVvd4+nNFr03PrEWv2QqiKxXtWCLZKEkXEREREZHSb/9m+KAXLJ8IoRHwr3fg7AchpBApTcdrIaaqqwH/+4uixaOp16SYKEkXEREREZHSbfM8N0DctkWuyfpV30K7AYU/TmQsdL7FPS5qbfqGme5n/U7+H0PEByXpIiIiIiJSei35Ckb2gYPboPqJboC4oiTGp14H0ZVh9yr4e7x/xzh8ALYtdo9Vky4BpiRdRERERERKH2vh1+fg86GQngInnAvX/ASVGxTtuJFxOWvTPRmFP8bGP8B6oFJ9qFinaPGI5KIkXURERERESgdrYedKmP0WfHgBTH3cre90MwwaA1HxgTnPqddDVCXY/Q/8/WXh98/qj94lMPGIZBMW7ABERERERKQcS94Da6bB6l9g9VRI3HRkW0gY9HkeOgwL7Dmj4l1t+tTHYfqz0LofhIQWfP+s+dHVH10CT0m6iIiIiIiUnPRU2DTXm5T/AlvmA/bI9tBIaNAZmvSA5udDtabFE8dp18OsV2HXStfvvU3/gu2Xngqb/nSPG6gmXQJPSbqIiIiIiBQfa90gbZlJ+brfIPVgzjI1WrqkvMlZrgl5REzxxxVVETr9G6Y96fqmt+pXsOncti6E9EMQXQWqNSv+OKXcUZIuIiIiIiKBlbwH1v56pAn7/o05t8dUcwl5kx7Q+CyIrxWcOE+7AWa9DjuXw9KvXbP3Y8lq6t4ZjCnW8KR8UpIuIiIiIiJF48lwc5mvmgKrfoYtf7nRzzOFRriktkkPt9RsXbBa6+IWXQk63QS/Pg2/PgstLz52XOqPLsVMSbqIiIiIiBRe4pYjSfmaaZCyL+f26i2gydkuKW9QQk3Y/dHpRpj9BuxcBssmQKuL8y7r8RwZ2V390aWYKEkXEREREZFjS0txtcirfnbN2Hcszbk9qqJrut70bJecl5X5w6Mre2vTn3G16SdemHdt+q6VcGgPhEVDQtuSjVPKDSXpIiIiIiJyNGth1ypvUj4F1s5wA6ZlMVDnFJeUNz0Hap8MoWU0veh0E8x+E3YsgeUToeWFvstlNnWv2wHCIkouPilXyuhvkYiIiIiIBFxGGmblD7TdOIqw1++H/Rtybo9N8CblZ7ta85gqwYkz0KIru0Hkpj/natNb9PVdm5590DiRYqIkXURERESkvDt8EOZ/DLNeJ2z/Rhplrg+NcAOkNT3HNWGv2er4HdG8080w+y3YvhhWfA8n9j26TGaS3kBJuhQfJekiIiIiIuVV0i6Y8zbMfRcO7QXAVqjO2uh21O8xjLAm3SEyNrgxlpSYKnDa9TDjBdc/vcX5OW9I7N8M+zaACYG6HYMXpxz3SsG8ByIiIiIiUqL2rIXvhsNLrWD6sy5Br9IY+r5E+i3zWVzvSuwJ55WfBD1T51sgIha2LYIVP+TcllmLntAWIuNKPjYpN1STLiIiIiJSXmxdCL+/Aku+OjKPee2ToOsdcOIFEBIKaWlBDTGoYqrAqdfBby+5udOb9z5Sm67+6FJClKSLiIiIiBzPrIW1v8JvL8OaqUfWNzkbut4Ojc44fvuZ+6PzrTDnHXdDY+WP0LyXW581P7qSdCleStJFRERERI5HngxY+o2rOd+6wK0zIdCqn0vOa2meb58qVIVTr3Xv269PQ7PzIGU/bF/itqsmXYqZknQRERERkeNJ2iFYMBpmvgp717p1YdFw8hDo/G+o3DCo4ZUJXW6DP96FLfPhn8nelRaqNIHYGkENTY5/StJFRERERIJt92qXEIK36bnJ+TjPdeTcvn2xG609aafbFF0ZTr3B9bOuUK2kXk3ZV6EadLzG3ej49WnXJQBUiy4lQkm6iIiIiEgw7VkL73SHw4mBO2bFem6k8pOHQESFwB23POlyG/zxHmye526igPqjS4lQki4iIiIiEizpqfDF1S5Br1gfKjdw660FbM7H1vvc52Pv84gK0P4KaN0PQsNL7GUcl2JruNr0Wa9Byj63TjXpUgKUpIuIiIiIBMuUR2DLXxBVCYZ9D5XqBTsiya7LbTD3PUhPgQo13FzyIsUsJNgBiIiIiIiUSyt/crW0ABe9rgS9NIqrCR2udo8bnq6p6qREqCZdRERERKSkJW6Br290j0+9Hk7sG9x4JG9nP+hGxG+hz0hKRlBr0o0x9xlj5hpjDhhjdhhjvjbGND/GPt2NMdbH0qKk4hYRERER8ZsnA768HpJ3Q0Ib6PlYsCOS/IRHw2k3QMU6wY5EyolgN3c/E3gd6AT0xNXs/2SMKcgQlM2BWtmWf4orSBERERGRgJn+PKybAeEVoP8oCI8KdkQiUooEtbm7tbZX9ufGmGHADuAUYPoxdt9hrd1XTKGJiIiIiATeut/cvNsAfV+Cak2DG4+IlDqlrU96Re/PPQUoO98YEwUsBR631k71VcgYEwlEZlsVB5CWlkZaWlpRYs1T5nGL6/gigaZrVsoaXbNSluh6lSzJuwn74hqM9eBpO5CMlv2gFF4XumalLCkr12th4jM2a47F4DLGGOAboLK1tls+5ZoDZwDzcMn3EOBGoLu19qjad2PMw8BDudePHj2amJiYwAQvIiIiIpIfazltzYskJC7kQGQtfm3+CBmhauYuUl4kJyczePBggIrW2sT8ypamJP114HzgdGvtpkLu+y1grbUX+tjmqyZ9065du4iPjy9KyHlKS0tj8uTJ9OzZk/Dw8GI5h0gg6ZqVskbXrJQlul4FIGTOm4T+/AA2NJL0YT9CzdbBDilPumalLCkr12tiYiLVqlWDAiTppaK5uzHmVeBC4IzCJuhes4ErfG2w1h4GDmc7FwDh4eHF/iGWxDlEAknXrJQ1umalLNH1Wo5t/gt+eRQAc94ThNc9KcgBFYyuWSlLSvv1WpjYgpqke5u4vwr8C9dcfa2fhzoJ2BqwwEREREREAiElEb4YBp40OPFC6HhtsCMSkVIu2DXprwODgYuAA8aYBO/6/dbaQwDGmKeAOtbaK73P7wDWAUuACFwN+iXeRURERESkdLAWJt4Be9dBxfpw4f/A26pTRCQvwU7Sb/L+nJZr/TBglPdxLaB+tm0RwPNAHeAQLlk/31r7fbFFKSIiIiJSWH99BH+PBxMK/d+H6MrBjkhEyoBgz5N+zFuJ1tqhuZ4/CzxbXDGJiIiIiBTZjmXww73u8dkPQL1TgxuPiJQZIcEOQERERETkuJKaDJ8Pg/RD0KQHdLk92BGJSBmiJF1EREREJJAm/Qd2LoPYmvCvtyFE/3KLSMHpG0NEREREJFD+Hg9/fQgY6PcOxNYIdkQiUsYoSRcRERERCYQ9a+HbO9zjbsOhcfdgRiMiZZSSdBERERGRokpPdfOhH06Eep2g+33BjkhEyigl6SIiIiIiRTXlEdgyH6IqwSXvQWiwZzoWkbJKSbqIiIiISFGs/BFmveYeX/wGVKoX3HhEpExTki4iIiIi4q/9m+Hrm9zjU2+AFucHNx4RKfOUpIuIiIiI+CMjzfVDT94NCW3h3MeCHZGIHAeUpIuIiIiI+OPnh2HjHIisCJd9CGGRwY5IRI4DStJFRERERApr6YRs/dBfhyqNgxuPiBw3lKSLiIiIiBTG7tXwzb/d4863wIkXBDceETmuKEkXERERESmotEPw+VVH5kM/5+FgRyQixxkl6SIiIiIiBfXDCNi2GGKqwaUjITQ82BGJyHFGSbqIiIiISEEsGA1/fQQYuOQ9iK8d7IhE5DikJF1ERERE5Fi2L4GJd7nH3e+DJmcFNx4ROW4pSRcRERERyc/hAzDuSkg/BE3OhjPuCXZEInIcU5IuIiIiIpIXa2HCrbB7FcTXgX7vQoj+hRaR4qNvGBERERGRvPzxLiz5CkLC4NJRUKFqsCMSkeOcknQRERERKVkbZsOKSa6WujTb9Cf8+H/ucc/HoN6pwY1HRMqFsGAHICIiIiLlyOy3YNJ/AAvN+8AF/4PY6sGO6mjJe+DzoeBJgxMvhE43BTsiESknVJMuIiIiIsXP44Gf7odJ9wIWMLDie3ijEyz/LtjR5eTxwJfXw/6NUKUxXPQaGBPsqESknFCSLiIiIiLFK/0wfHktzHzVPT/7IbhxBtRoBcm7YMxg+ObfbhT10uC3F2HVZAiLgss+gqiKwY5IRMoRJekiIiIiUnwO7YOP+8Hf493ga/96G7rdBQlt4Pqp0OU2wMD8T+DNrrB+ZnDjXTsdpj7hHvd53sUpIlKClKSLiIiISPHYvwk+6AXrf4OIOLj8C2g38Mj2sEg49zEY+h1UrA/71sPIPjD5QVf7XtISt8IXV4P1QPsr4OQhJR+DiJR7StJFREREJPC2/Q3v9YSdyyCuFlz9AzQ5y3fZhl3hpt9dYoyF31+Bd3u4Y5SUjHQYfw0k7XTN8Ps8V3LnFhHJRkm6iIiIiATWml9hZG84sAWqt4BrJh+72XhUPFz8Ogz4FGKqwva/4d2zXMLuySj+mH95DNb/7mr8L/sIImKK/5wiIj4oSRcRERGRwFn0OXxyCRxOhAZd4epJUKlewfc/sS/cPBua9YaMVNf0fVRf2Luu2EJm+ffw+8vu8UWvQbWmxXcuEZFjKHSSboxpkMf6cGPM00UPSURERETKHGvht5fcKO6eNGj1L7jiS4iuXPhjxdaAQZ/Bha9CRCxsmOkGlZv/iTtPIO1dB1/f6B6fdhO0ujiwxxcRKSR/atJ/M8Y0z77CGNMBWAD0DURQIiIiIlKGeDLg+7vh54fd8863wCUfQHiU/8c0Bk6+Em78Dep1gtSDbpq2MZfDwZ1Fizf9sEvO18+CcVdByn6o2xF6Plq044qIBECYH/t8AMwwxpwH/A08CtwBvAw8FLDIRERERKT0SzsE46+F5RMBA+c9CZ1vDtzxqzSCYd/DzP/BL0/Aiu9g0x9wwf+gRZ+cZa2FlH1ulPbELa5PfOLWXD+3QPLunPtFV4H+IyEsInBxi4j4qdBJurX2IWPMPmAqsBmwwBnW2rkBjk1EREREAiUjHVb/AhWqQY0TITy66MdM2g2fDXRJc2gk9HvbNXMPtJBQOP1OaHoOfHkD7FgCYwbBiRdAWFTORDz9UMGOGRrhRp2v3AB6PFC4fvMiIsXIn5p0rLUvGWMSgbeAAUrQRUREREq5mf+DKY+4xyYEqp4ACa2hZms38nrN1hCX4JqZF8SetfBpf9i9CqIquT7kDboUW/iAi/P6qfDL4zDzVVj2re9y0ZUhvo5LwuNrQVzto3/GVCn4axURKUGFTtKNMbdlezodGG2MeQrYC2Ct/V+AYhMRERGRQLAW/vrIPY6Idf27d61wy9/jj5SLqQo1W0HNNkcS+Ootjm4GvvkvGH2Zm1O8Yj24YjxUb06JCIuEcx+DFn1h5Q+uqXp87WwJea3AtBIQEQkSf2rS78z1fCsw1PvYAkrSRUREREqTjXNg71qXoN+9ElIS3Tzk2xZ7f/4Nu/9xfbXXTndLppAwqNb8SNIeGQs/3g9pSS6Zv/xzlxyXtPqnuUVE5DjjT5/0RsURiIiIiIgUkwWj3c+WF0FEBbfE14ITeh4pk3YIdiw7krRv9y4p+10f8B1LgLFHyjc+Cy77CKLiS/SliIgc7/zqkw5gjIkAGgGrrbXpgQtJRERERAIm7RAs+co9bjco73Lh0VDnZLdkshb2b8qWuC+GXaug8ZlwziMaDV1EpBj40yc9BngVuMq7qhmwxhjzP2CLtfbpAMYnIiIiIkWx/Ds4nAgV60ODroXb1xg36nmletC8d/HEJyIiOYT4sc9TQDugO5CSbf3PwIAAxCQiIiIigbJwjPvZbgCE+POvn4iIlCR/mrtfjJt2bbYxxmZbvxRoEpCoRERERKToDmyD1VPc4/yauouISKnhz+3U6sAOH+sr4EZ3FxEREZHSYNE4sB6odxpUVV2KiEhZ4E+SPhc4P9vzzMT8OmBWkSMSERERkaKzFhZ+5h63GxjcWEREpMD8ae5+HzDJGNPSu//txphWQGfgzEAGJyIiIiJ+2roQdiyF0Eho1S/Y0YiISAEVuibdWjsT6ArEAKuBc4HtQGdr7bzAhiciIiIifskcMK5FH4iuFNRQRESk4PyaJ91au5gjU7CJiIiISGmSkQaLP3eP2w0ObiwiIlIoha5JN8b0Mcac52P9ecYYTaApIiIiEmz/TIbkXVChBjTpEexoRESkEPwZOO5pINTHeuPdJiIiIiLBtHC0+9n2Mgj1q+GkiIgEiT9J+gm4OdFzWw40LVo4IiIiIlIkyXtgxST3WHOji4iUOf4k6fuBxj7WNwWSihaOiIiIiBTJ3+PBkwYJbSChdbCjERGRQvInSZ8AvGyMaZK5whjTFHjBu01EREREgiVrbnQNGCciUhb5k6Tfg6sxX26MWWuMWQssA3YDdwcyOBEREREphJ0rYfM8MKHQpn+woxERET8UeiQRa+1+Y0wXoCfQDjgELLLWTg90cCIiIiJSCJm16Cf0hNgawY1FRET84u886Rb4ybuIiIiISLB5MmDRWPdYA8aJiJRZ/jR3FxEREZHSZu10SNwMURWhee9gRyMiIn5Ski4iIiJyPMhs6t76EgiLDG4sIiLiNyXpIiIiImXd4QOw7Fv3WKO6i4iUaUrSRURERMq6pRMgLRmqNoW6HYIdjYiIFEGhB44zxrTNb7u1dpH/4YiIiIhIoWXNjT4IjAluLCIiUiT+jO6+ALBA5l8A6/1pvI9Dix6WiIiIyPHBrJ5CrX1zgT7Fc4K962HdDMBA2wHFcw4RESkxfk3BBpwG7MQl5n/j/uqsD1RQIiIiImWetfDbi4RNeZRTgYw/60LnGwN/nsxp1xp1g0r1An98EREpUf4m6RustTsAjDEWSLbWKkkXERERAZegT34QZv4va1XIT/dB5frQIoA16tZma+quAeNERI4H/gwctwNoBmCMqQ1UAL43xvQKZGAiIiIiZZInA769LStBzzjnUdZVPRNjPfDF1bB5XuDOtfEP2LMGwivAiRcE7rgiIhI0/iTpk4Axxpi3gF+AycBVwMfGmIcDGJuIiIhI2ZKe6hLxvz4CEwIXvobntJtZVO8qPI17QPohGD0A9q4LzPkWjnY/W14EkbGBOaaIiASVP0n6v4GPgHrAz8AQa+0PwKnAhQGMTURERKTsSE2CzwbC0q8hJBwuHQUnDwHAmjAy+r0PCW0gaSd8eikk7yna+dIOwd9fucftBhbtWCIiUmoUOkm31iZZa//PWnu+tfaWzL7p1tq1QOeARygiIiJS2h3aBx/3g9VTIDwGBo91tdvZRcbB4M8hvg7sWgljr4D0w/6fc8UPcHg/VKwHDbsVKXwRESk9/KlJz5O1tgh/aURERETKoIM7YFRf2DgboirCkK+h6dm+y8bXgss/h8h4WP87fH0zeDz+nTdzwLi2AyAkoP/SiYhIEBV6dHdjzJf5bbfW9vM/HBEREZEyZN8G+Ohi2LMaKtSAIV9BQuv896nZCi77CD7tD39/AZXqwzkPFe68B7bDqinucbtBfoUuIiKlkz+3XS8GzgYOAvt9LAVmjLnPGDPXGHPAGLPDGPO1MaZ5AfY70xgzzxiTYoxZY4wphklHRURERPKxcyV80Msl6BXrw9WTjp2gZ2pyFlz4qnv824vw58jCnXvxOLAZULcjVGtauH1FRKRU8ydJ7wmsBToAX1hrh2VfCnmsM4HXgU7e44YBPxljKuS1gzGmEfA9MAM4CXgS+J8x5pLCvxQRERERP2xZACN7QeJmqNYcrvkRqjYp3DHaD4Yz/+Mefzcc/plc8H0XjnE/VYsuInLc8WfguCm45Pg54G1jzM/GmHb+nNxa28taO8pau8RauxAYBtQHTslntxuBDdbaO6y1y6y17wEfAHf7E4OIiIhIoaz73fVBT94NtdrDsB8gvrZ/x+r+H2g32NWKj7vKJf/HsnURbP8bQiOhtXoZiogcbwrdJx3AWmuBkcaYMcA9wK/evur3W2u3FCGeit6f+c1J0hn4Kde6H4FrjDHh1tq07BuMMZFAZLZVcQBpaWmkpeUoGjCZxy2u44sEmq5ZKWt0zUqwmH9+IvTLqzHpKXjqdyHjsk8hIg7yuRaPeb32fp7Q/ZsIWTcd++mlpA/7CSrWzfN4IfM/IRTwNOtFRlhsvucW8Ye+Y6UsKSvXa2HiMy7fLjhjzG0+VtfGzZ+OtTauUAc8clwDfANUttbmOY+IMWYlMMpa+2S2dV2A34Ha1tqtuco/DBw1Gsvo0aOJiYnxJ1QREREph+rsmcXJ698hhAy2xp/En43+jSckIiDHDstIptvKx4lP2URiVB1mnHA/6WFH9/4zNp3z/r6dyPQDzG58F9srtg/I+UVEpHglJyczePBggIrW2sT8yvpTk35nHut3+XGs7F4D2gKnF6Bs7jsLJo/1AE8BL2Z7HgdsOvfcc4mPjy90kAWRlpbG5MmT6dmzJ+Hh4cVyDpFA0jUrZY2uWSlpIfNGEjL/LQwWT+v+VOv7Kr1CC3btFfh6TeyMHXke8Qc30/vAaDIGjoXQnDcBzD8/ErbgALZCdU657B4oYAwihaHvWClLysr1mpiYb16eQ6GTdGtto8LucyzGmFeBC4EzrLWbjlF8G5CQa10NIB3Ynbuwd+72rPnbXYU9hIeHF/uHWBLnEAkkXbNS1uialWJnrRt9fcqj7nnH6wjp/SwhfsxLfszrtWpDN4f6yN6ErJtByA/D4eI3wZgjZf4eB4BpcxnhUWoRKMVL37FSlpT267UwsfkzunvAGOc1oB/Qw1q7tgC7zcKNBJ/ducCfufuji4iIiPjt0D748b9HEvRud0Of58CPBL3AarWFSz8EEwoLP4NpTx3ZlrwHVvzgHrfXqO4iIserQtekG2NezG+7tfauQhzudWAwcBFwwBiTWUO+31p7yHu+p4A61torvdveAm7xxvEubiC5awD9tRIREZGiSU+FVZNh0VhYMQkyvI3xzn0cutxaMjGccA70fRG+vR1+fQYq1YeTroAlX0JGKtRsAwltSiYWEREpcf70ST8p2+PTgXnAIe/zwo1CBzd5f07LtX4YMMr7uBZuWjZ3AmvXGmP6AC/hBqvbAtxmrR1fyHOLiIiIuCbtG+e4xHzJV3Bo75Ft1VvAGfdAm/4lG9MpQ2HfBpjxgkvW42tnmxt9YMnGIiIiJcqfPulnZT42xhwABltr1/hzcmutKUCZoT7W/Qqc7M85RURERADYuRIWj4NF42Df+iPrYxNcUt52gKuxNsf8d6V49HjAJeqLP4cxV0BakmsG3/ay4MQjIiIlwq950kVERETKpIM74O/xrtZ8y/wj6yNi4cQLXQLc6AwICQ1ejJmMgYteh8StsP43t67pORBbI7hxiYhIsVKSLiIiIse31CRY/p1LzFdPBZvh1ptQl/S2vQya94GIUjhaelgkDPwE3j8Pdq1wzeBFROS45s/AcRdmexoCnG2MaZ25wlo7IRCBiYiIiPgt/TCsneGasy+b6JqKZ6rTwTVlb90PKlQLXowFFV0Zrv0ZdiyF+p2CHY2IiBQzf2rSv871/O1sjy1QCtqHiYiISLlirUtiV0+FNVNh/UxISz6yvXIjl5i3vQyqNglenP6KileCLiJSTvgzcFxQ51YXERERAeDANlgz7UhifnB7zu0VakDLi1xyXrdD8AaAExERKYQi9Uk3xkRZa1MCFYyIiIhInlKTXA15ZlK+Y2nO7WHR0LArND4LmpwFNVoqMRcRkTLHnz7pocD/ATcCNY0xzay1a4wxjwHrrLXvBzpIERERKYc8GbB1gTcpn+bmMs9IzVbAQK12LiFvfJZrDh4WGaRgRUREAsOfmvT/AlcBI4B3s61fDNwJKEkXERER/yTvgZU/wspJsPZXOLQ35/aK9aFJd5eUN+4OMVWCEaWIiEix8SdJvxK43lo7xRjzVrb1i4AWgQlLREREyo0D22H5RFj2LaybAZ70I9si49285Y27Q5MeUKWxmrCLiMhxzZ8kvQ6wysf6ECC8aOGIiIhIubB3/ZHEfMNs3AQxXjVbQ4vz3RzmtU+G0CINoSMiIlKm+PNXbwnQDVifa/2lwPwiRyQiIiLHp50rYdkEt2xdmHNbnQ5w4gVuKYtTpImIiASIP0n6I8DHxpg6uNrzfsaY5rhm8H0DGZyIiIiUYdbCtkWwdIKrMd+14sg2EwINurqkvMX5ULFu8OIUEREpRfyZJ/1bY8wA3AjvFngU+Au4wFo7OcDxiYiISFni8cCmP1xSvmwC7NtwZFtIuOtbnpmYV6gWtDBFRERKK786eVlrfwR+DHAsIiIiUpbtWgXjhuScvzwsGk44B068EJqdB1EVgxefiIhIGaCRWERERKToVv4E46+Bw4kQEQfNe7sa86bnQERMsKMTEREpMwqdpBtj9pJjCNacrLWasFRERKS8sBZ+exGmPAZYqNcJLvsI4moGOzIREZEyyZ+a9Du8Pw3wJvAgsCNQAYmIiEgZkZoEX98MS792z08ZBr2fhbCIoIYlIiJSlvkzcNyHmY+NMa8C4621awIalYiIiJRue9fBmMth+99uQLg+z0KHq4MdlYiISJmnPukiIiJSOGumwedD4dBeqFDDNW9v0DnYUYmIiBwXApGk59k/XURERI4j1sLsN+Gn+8FmQO2TYMCnULFOsCMTERE5bvgzcNyX2Z5GAW8ZY5IyV1hr+wUiMBERESlF0g7BxDth4WfuebtB0PclCI8OblwiIlKufbNwKyv3Gs5J9xAeHuxoAsOfmvT92R5/EqhAREREpJTavxnGXg5b5oMJhfOegNNuBGOCHZmIiJRjGR7Lsz+uZMeBUDqu2U3PVrWDHVJA+DNw3LDiCERERERKofWzYNwQSNoJ0ZXh0lHQuHuwoxIREWHuuj3sOHCY6FBLl8ZVgx1OwGjgOBERkbLOWkjc4pLoiJjAHffPD+D7EeBJg5qtYeCnULlh4I4vIiJSBN8t2gpA2yqWiLCQIEcTOP70Sd+T33ZrbRX/wxEREZFC2b8Zvr0NVv0MJgSqNIGaLV1SXbOVWyrWh5BC/POSngo/3APzRrnnLS+Gi9+AiArF8QpEREQKLcNj+eFvl6SfVO34Gsvcn5r0SsAd5OybLiIiIiXJWpj/Cfz4f3A40bvOA7v/ccvSb46UjYiFGi2PJO01W7nn0ZWOPu6B7TDuStg4GzBw9oNw+p3qfy4iIqXKnDW72XUwlUrR4TSLTw92OAHlb3P3MdbaHQGNRERERApm/yb49nZXew5Qp4Or6Y6qBNv/hu1LYMdS93jnCkg9CJv+cEt2FesdSdhrtoLIOPj2DjiwBSIrwiXvQbNzS/rViYiIHNPExa4W/dyWNQgNWR/kaALLnyTdAnHGmAPW2kOBDkhERETyYC3M/xh+/K+rPQ+NhB7/hc63QEioKxNXE5qefWSfjDTYvcol7tmXxE2wf6NbVk7KeZ5qzWDgZ1Ctacm9NhERkQJKz/Aw6e9tAPRunUDiSiXpBlgJYIzxANuB+cD71tqvAxeaiIiIZMmr9rx68/z3Cw2HGie6pU3/I+sP7YUdy7xJu7f2ffdqaHIW9H0ZouKL7aWIiIgUxew1e9iTlEqVChF0alSZn1YGO6LA8idJPwuXqIcD8UBtoCPwuTHmemvtyADGJyIiUr4VpPbcH9GVoUEXt4iIiJQhExdtAaBX6wTCQo+fUd0z+TNP+q++1htj/gLuApSki4iIBML+TTDhNlg9xT2v2xEuegOqNwtuXCIiIkGSluFh0hLX1L1vm1pBjqZ4BHKe9HeBdQE8noiISPlkLfz1kas9Tz3grT2/Hzr/u2i15yIiImXczNW72ZecRrXYCE5rXBVPxvE1sjsUIUk3xlQHmuMGkltprd0JfB2guERERMqnfRvdvOerf3HP654KF72u2nMRERFg4kLX1L1361qEhhg8GUEOqBgUOkk3xlQAXgWGAJm38zOMMR8Bt1prkwMYn4iISPmQu/Y8LMrVnne6WbXnIiICwF1jF7B6VxKfXnsasZGBbBRdNqSme/jR29T9/LbHZ1N3AH962b8InAlcCFTyLhd5170QqMBERETKjX0b4ZN+rgY99YCrPb/xN+hyqxJ0EREBYOmWRL6cv5mFG/cxYcGWYIcTFL+v2kViSjrV4yLp2LBKsMMpNv7cfrkE6G+tnZZt3ffGmEPAOOCmQAQmIiJyXEs7BBtmw5ppMPd91Z6LiEi+xv25Mevx2D83Mvi0+kGMJjgmLtoKwPltXFP345U/SXoMbm703HZ4t4mIiEhungzYsgDWTIW1v8KGOZBx+Mj2uqe6ec+rnRC0EEVEpHRKScvgy782ZT1fuHEfK7YdoHlCXBCjKlmH0zP4aenx39Qd/EvSZwGPGGOutNamABhjooGHvNtERETEWti1Etb86mrL1/0Gh/fnLBNXCxp3h6bnQKt/qfZcRER8+nHJNhJT0qlTKZqWteOZvHQ74/7cyAN9WwY7tBIzY+UuDqSkkxAfxSn1Kwc7nGLlT5J+OzAJ2GSMWYgb3b09kAKcF7jQREREypj9m10t+Zpf3c8DW3Nuj6wIjbq5xLzRma7W3By/zfVERCQwxvzhmrpf1qEebeq6JP2r+Zu5t1cLIsL8GWas7Plusfub2qdNLUKO46bu4EeSbq392xhzAnAF0AIwwBjgU2vtoQDHJyIiEnjbl8LEO+DgdgivABExEB4DERW8P2PyWO9j+541rqZ8za+w+5+c5wmNhPqdoPGZLjGv1V615SIiUijrdiUxa81ujIFLO9SlRlwkNeIi2XHgMD8v206fNsd3029wzf0nL3U9ro/3pu7g5zzp3mT83QDHIiIiUvw2/QmfXAIp+wJ/bBMCtU9yteSNz4R6p0F4dODPIyIi5cZY74BxZzarTu1K7m9K/1Pq8sa01Yz7c2O5SNJ/XbmTg4fTqV0xipPqVQp2OMXOn3nSL8xvu7V2gv/hiIiIFKM1v8JngyAtCep2hJ6PQnoKpCZDWjKkJrlR19OScq1L9j73sT66ikvIG50JDU+H6ErBfpUiInKcSMvw8MU8N2DcwI5HRnO/rEM93pi2mukrd7J1/yFqVTy+bwh/t6j8NHUH/2rSv85nmwXUjk9EREqf5d/B58PciOqNzoSBoyEyNthRiYiI5Gnq8h3sPHCYarERnH1ijaz1DatV4NRGVfhj7R6++HMTt559/M4MkpKWwc/LXFP3vu1qBzmakuHvKAMJ1toQH4sSdBERKX0WjoWxQ1yC3qIvDB6nBF1EREq9sXNdU/dLTqlLeGjO1G1Ah3oAfD5vEx6PLfHYSsrU5TtITs2gTqVo2tWtGOxwSkT5GApQRETKrz/eha+uB5sB7QbBpR9CeFSwoxIREcnXtv0pTF2xAziSkGfXp00tYiPD2LAnmdlrd5d0eCVmondU975ta2HKyYwoStJFROT4NeMF+P5u9/jUG+CiNyDUrzFTRUREStQX8zbisXBqoyo0rn5066/oiFAu8Db/HuetcT/eJKem88syd6OiPIzqnsmfJN0CccaYeF9LoAMUEREpNGth8kMw5VH3/IwR0PsZCNG9aRGR8qYsNgX3eGzWqO4DOx5di55pgHfbD39vY/+htBKJrST9snwHh9IyqF8lhjZ1ykdTd/AvSTfASmBvrmWf96eIiEjweDJg4p3w+8vu+bmPQ4//QjlpIiciIkc8/cNy2j7yE29MW1WmkvVZa3azcc8h4qLC6N067xrkdnUr0rxmHIfTPUxYuKUEIywZmaO6n1+OmrqDf0n6WUAPH0vmehERkeDISIMvr4d5IwEDF/wPutwa7KhERCQIJi7awlu/rubg4XSenbSCK96fw7b9KcEOq0A++2MDABe3r0N0RN5jcxtjuLRDXeD4a/KedDidX5Z7m7qXg7ngsyt0km6t/TW/pTiCFBEROaa0QzDmcvj7CwgJh/4fwClXBTsqEREJgnW7kvjP+MUA9GhRg5iIUGau3k2vV6bz05JtQY4uf3uSUvlpiZtybEA+Td0z9Tu5LuGhhsWb97N0S2Jxh1dipizfweF0D42qVaBV7fLVq7rQSbox5oz8luIIUkREJF8pifBJf/jnRwiLhkGfQet+wY5KRESC4HB6Brd89hcHD6fTsWFl3hlyChNvPZ3WdeLZl5zG9R/P4/6vF5OSlhHsUH36av5mUjM8tK4TT+sC9MOuUiGCni1rAjDuz+OnNn2it/n++W3KV1N38K+5+7R8lqkBiElERKTgknbDRxfC+t8gMh6GfAkn9Ax2VCIiEiRPfreMvzcnUjkmnP8NOomw0BAaV4/ly5u6cv0ZjQH4ZPYGLnj1N5ZvK101z9Zaxs51Td0HdKxf4P0u9U7R9vWCzRxOL503HwrjQEoa01buBMrXqO6Z/EnSK+ezVAlcaCIiIseQuBVG9YEt8yGmKlz1LTToEuyoREQkSL5fvJUPZ60H4MXL2lOrYnTWtoiwEP6vz4l8dPWpVIuN5J8dB7nwtd/5cOY6rC0dg8rN37iPldsPEhUewkXtaxd4vzNOqE5CfBT7ktOYvHR7MUZYMqYs20FquofG1SvQIiEu2OGUOH/6pO/PXIBQ4H/ADOB1ICLA8YmIiPgUc3gHYR/3hZ3LIa42DPsBarcPdlgiIhIkG3Ync+8XiwC44czGnNWihs9yZzSrzqQ7utGjRQ1S0z08NGEJ13z4J7sPHi7JcH0a+4drrn5+m9rER4UXeL/QEEP/U9wAcmOPgwHkJi5yTd37tq1d7pq6g3816dm9AJwGjAWa4RJ2ERGR4rVjGd1WPo7Ztx4qN4KrJ0H15sGOSkREgiSzH/qBw+mc0qAyd5+b/9+EarGRvH9VBx6+oCURYSH8snwHvV6ZwYx/dpZQxEc7eDidb73J6cBTjz1gXG6XeZu8/7ZqF5v2Jgc0tpK0/1Aa01fuAqBvOWzqDkVP0rsDN1prnwAuB84uckQiIiL52baYsE8uJCp9H7b6iS5Br9wg2FGJiEgQPf3DchZt2k8lbz/08NBjpznGGIZ2bcQ3/+7KCTVi2XngMEPe/4Mnv19GarqnBKLOaeLCLSSnZtC4egU6NKhc6P3rV42hc+OqWAvj520uhghLxs9Lt5Oa4eGEGrE0q1n+mrpD0ZP0qsAG7+MN3uciIiLFIz0Vvrwec2gve2KakD5kAsQlBDsqEREJokl/b2Pk7+sAeOHSdtSpFJ3/DrmcWCueCbeczuWnuYHa3pm+hkvenMmanQcDHWq+xnibqQ/sWM/vJt6XdXRN3j+ftxGPp3T0sy+s7xZvBVxT9/LKnynY4jMX76pY7+Njzw8gIiJSFL+9BDuWYmOqMafJXRBd+JoGERE5fmzck8yILxYCcF23Rpx9Yk2/jhMdEcoT/2rD20NOoVJMOIs376fvq78x7s+NJTKo3PJtiSzYuI+wEEO/k+v6fZzerWsRFxXGpr2HmLl6dwAjLBn7k9Oyuhyc37b83oT3pyZ9H7DXu8QC872PtwUuLBERkVx2LIfpzwGQce6TpIaVzyZwIiLipKZ7uOWz+SSmpHNS/UqM6NWiyMc8r1UCk24/g86Nq5KcmsGILxZxy2fz2X8oLQAR522Md8C4ni1rUi020u/jRIWHZo0KXxbnTP9x6TbSMiwtEuJoWqP8/p33J0k/C+jhXXw9FhERCSxPBky4BTxp0KwXtuW/gh2RiIgE2bOTlrNw4z4qRofzagH7oRdEQsUoPrn2NEb0ak5YiOG7RVvp88oMFm3aF5Dj55aSlsFX810f8gEdCz9gXG6ZA8hNWrKN/cnFe3Mh0L5b5Jq6n9+mfA4Yl8mfKdh+zW8pjiBFRKSc++Nd2DQXIuLg/BehHE7HIiIiR0xeup33flsLwHP921K3ckxAjx8aYri5e1O+uKkL9avEsHnfIS5/bw6LN+0P6HkAflyyjf2H0qhdMYpuJ1Qv8vHa1KlIi4Q4UtM9fL2g7Awgtzcpld9XuVHdzy+no7pn8ut2kzGmuTGmjvfxWcaYV4wxN5ryOImdiEh5kZrkBm4raXvXw5RH3OOej0DFOiUfg4iIlBqb9iZz9+euH/o1pzfi3FbF13e5fb1KfHfb6XRsWJkDKekM+WAOy7YmBvQcmfOaX9qhHqEhRU+njDFZNfJlqcn7j0u2ke6xtKwVT+PqscEOJ6j8GTjuLmAZsMYYcxPwNdASeAZ4MqDRiYhIyfJkwJ618M9kmPUGTLwTRvWFF1rAk7XhtVMgcUvJxWMtTLwD0pKhQVc4ZVjJnVtEREqdtAwPt3r7iLerV4l7A9AP/VjiosL5YGhH2terxL7kNK54bw7/bD8QkGOv353EzNW7MQYu7eD/gHG5Xdy+DhGhISzZksjfmwNf+18cMkd1L++16ABhfuxzK3AXsBH4FLjKWjvWGNMHeAu4L4DxiYhIcUjeA7tXwa5/YPc/3p+rYM8ayMintnzfBhg9AIb9AJElcJd74RhY/QuERsIF/4OQwPQ3FBGRsun5H1cwf8M+4qLCeG3QSUSElczfhbiocD68+lQuf282f29OZPB7cxh7faci1/hm1nR3O6F6QJvsV64QQc9WNflu0VbG/bmR1nVK90Rcuw8ezhqNvq+SdL+S9LrAOGvtFmPMJ8A87/r5gN5REZHSJiMdFnwKG/9wifjufyA5n2lZQiOhahOo2tQt1U6AqidAeBR8dDFsWwTjr4GBoyEktPjiPrgDJv3HPT7rPqjWtPjOJSIiAMxbv4drP/yTOpEhNDwpkXb1qwY7pCy/LN/O29PXAPBc/3bUqxLYfujHUjE6nI+vPo1B785m+bYDDH53DuNu6Ez9qv7FkZ7h4fM/NwEwKAADxuU2oEM9vlu0la/nb+b/+pxIVHgx/s0uoklLtpHhsbSpU5EGVSsEO5yg8ydJDwUyhwlMBzK8jz342cddRESK0Y//B3+8ffT6+DpHJ+LVmkLFenkn34PGwId9YeUkd9zezxRf3D+MgJR9kNAWOt9afOcREZEsI39fx97kNPYmh3DRG7Pp0yaBO85pRrOawZ0Oa8u+Q9w1zvVDH9qlIb1aB2cO7coVIvjk2tMY+M5sVu04yKB3ZzPuxs7UqRRd6GNNW7GTHQcOU7VChN/zu+ena9Nq1K4YxZb9Kfy4ZBsXtS+9Y7pkjequWnTAvyQdYIoxJh2IBr41xqQW4VgiIlJc5r53JEHvchvUaucS8ipN/GuuXq8j/Ott+PwqmPMWVG4EnW4MbMwAy7+DJV+BCYWLXoNQ/YkRESluh9MzmLZiJwDNKnr4JzGE7xdv44e/t3Fhu9rcfvYJQRnQK7Mf+r7kNNrUqch9fYq/H3p+qsVGMvra0xjwzmzW7kpi8LuzGXdDZ2rGRxXqOGO8A8ZdckrdYmm2Hxpi6N+hHv+b8g/j/txYapP0nQcOM3uNa+FX3qdey+TP1fAIMB74BngM+Nz7eDzwaGEOZIw5wxjzrTFmizHGGmMuPkb57t5yuZfg/qaKiJRGq6fC9yPc4x4PwLmPQZv+LlEvSn/yVhfDOd7R1n+8D1ZMKnKoOaTsh++Gu8ddvTcWRESk2M1avZuDh9OpERfJTSd6mPjvzvRqlYC18M2CLZzz4q/c/flCNu5JLtG4XvhpJfPW7yUuMozXB59MZFjwm23XiI9i9HWnUa9KNOt3JzP43dnsPHC4wPtvT0xh6oodwJF5zYvDpae4weh+X7W7xD+3gpr091Y8FtrVq1TiXRhKK3/mSX8kv6WQh6sALARuKeR+zXH93zOXfwq5v4jI8W3XKlfbbTOgzWXQbXhgj9/1djj5SrAe+OJq2LowcMee/CAc2Opq+8+8N3DHFRGRfP20dDsAZ7eoToiBZjXjeGvIKUy89XTOblEDj4Uv5m3irOencd+Xi9my71CxxzR1xQ7e+nU1AM/0b+t3/+/iUKtiNKOv7UTtilGs3pnEFe/NYU9SwaYq/WLeJjI8lo4NK9O0RvG1TqhXJYauTd24Ap/P21Rs5ymKid6m7n1Vi54lqH3IrbU/WGvvt9Z+Wchdd1hrt2VbMo69i4hIOXFoL3w2wNVI1+0IF74KpujzruZgDJz/IjTuDmlJbsT3/ZuLfty1M2DeKPf4wlchvPB9/EREpPA8Hstkb5Le88QaOba1rlOR94d25Kubu9DthGqkeyyf/bGB7s9N46Fv/mZHYkqxxLRtfwrDvf3Qr+zcgD6lMImrVyWG0dd1omZ8JCu2H+CK9+awPzkt3308Hps1N/qAjvWLPcbMmvov/txIhscW+/kKY0diCn+s2wNA7zbBGWegNCqrnfzmG2OigKXA49baqXkVNMZEApHZVsUBpKWlkZaW/y+QvzKPW1zHFwk0XbPHkYw0QsdeScjuVdj4OqRf8iEQCsX12f7rA8I+7I3ZtQL76WWkX/ktRPo5uFBaMmETbsUAGScPxVPn1Dzj1jUrZYmuVykL5m/cx84Dh4mNDOPkenH8+s/R12zrWrF8cOXJ/Ll+Ly9PWcWctXv5cNZ6xszdyOWn1uP6bg2pGhuZxxnytzsplTU7k1i9M4nVOw+yemcSS7YmsicpjZa14hjRs2mp/R2qUzGCD4d24IoP5rJ0ayJD3p/NqKGnEBcV7rP8rDW72bAnmdjIMHq2qFrsr+vsZlWJjwpjy/4Ufl2xjW5NqxXr+Qpj4sLNWAvt61WkZmy4X+9FWfmOLUx8xtrScTfFGGOBf1lrv86nTHPgDNy0b5HAEOBGoLu1dnoe+zwMPJR7/ejRo4mJKT3NZUREAqHtxg9ptGsK6SGRzDjhARJjiv8OffThnZyx8lGi0vezLb4dfzS+A2sK31+w5eYxnLDjew6FV+aXE58mPVS16CIiJWXC+hCmbAnh5KoermrmKdA+K/cbvt8YwtoDrrVWRIjljARLj9oeKvjITz0W9qXC9mTDtkOw/ZDxLpCU7rvFV1y45fZWGVQvA38StiTDa0tCSUo3NIqz3HRiBpE+/hx+uDKEv3aH0LWmh8saF+y9Lqov1oQwY3sIJ1X1MLSAn29JeOXvUNYcMPyrYQbda5WOvLS4JCcnM3jwYICK1trE/MqWqSQ9j/2+Bay19sI8tvuqSd+0a9cu4uPj/Q03X2lpaUyePJmePXsSHu77DppIaaJr9vgQ8uf7hP54LxZDxqUfYZv1LrFzm81/EfrJRZj0Q2Sccg2e854uVBN7s2U+oaPOw1gP6Zd+gm3WK9/yumalLNH1KmXBea/8xppdybx8WVvObVG1wNestZYZq3bz8pRVLN7s8o4KkaEM69yAFglx3prxJFbvOsianUkcSss7QaxTKYom1SvQpHqs92cFTkyIo0Jk2Wn8u2RLIleO/JPElHROa1SZd684meiII5n63uRUuj77K2kZlq9u7ETrOsWTj/iK6+I3ZxMeavh9xJlUjokokfP6Yq3lj3V7+Xj2Bn5c6gbPm373GdSqWLjR8TOVle/YxMREqlWrBgVI0svOFZ+32cAVeW201h4GsoZaNN5/GsPDw4v9QyyJc4gEkq7ZMmzVFPjp/wAw5zxMWCuf9y2LT8PToN87MO5KQue9T2j1E6DTTQXbNyMNvr/TDULX+hLCWl1Q4NPqmpWyRNerlFardhxkza5kwkMNZ7dMINybUxb0mj27ZS16nJjAz8t28OLklSzbmshr09b4LBseamhYtQJNa8RmLU2qx9K4egViIsp+atK+QVU+vuY0rnhvDnPW7uXfYxby7pUdiPK+qd/9vYm0DEvLWvG0b1AlKzcpibha1Y5nyZZEvvt7B8O6NiqR82aXnJrO1/O38NGsdSzfdiBr/dAuDalfzc+uctmU9u/YwsRW6N8EY0y+g7xZa/sV9phFdBKwtYTPKSJSeuxcCZ8PcyO5txvsRl4PhpYXQs9HYfIDMOk+qFQfWpx/7P1+fwW2/w3RVaDXM8Ufp4iI5PDT0m0AdGlSjbgo//oFG2Po2bImZ7eowY9LtvH+b2tJzfDQtHosTbIl5PWrxBAeGtSxq4tdu3qVGHV1R4a8/wcz/tnFTZ/M4+0hHQgPNYz5ww0YN/DUeiWWoGe6rEM9HpqwhLFzNzK0S8MSO/+G3cl8NGsd4/7cSGJKOgDR4aH0O7kOV3ZuSPOEoifoxxt/blddDIwDMudcGAx8CxzIa4e8GGNigabZVjUyxrQH9lhrNxhjngLqWGuv9Ja/A1gHLAEicDXol3gXEZHyJ3kPjL4MDu+Hep3ggpcDP5J7YXS5FfasgXkjYfy1MOx7qH1S3uV3roRfn3WPez0NsdVLJk4REcny0xI3qvu5rWoW+VghIYbebWrRuxSOxF6STmlQhQ+GdmToyD+YumInt4z+i+vPaMyK7QeIDAvhovZ1Sjymi9vX4Ynvl7F82wEWb95P27qViu1cHo9lxqpdfDhzHVNX7CCzh3WDqjEM6dSASzvUo2J06a31DjZ/25TcZq3dAWCM6Q+MsNb6btOSvw5A9pHZX/T+/BAYipsDPfuoRxHA80Ad3E2CJcD51trv/Ti3iEjZlp4K466EvWtdrfXATyHMv1F1A8YY6PM87NsAq6fA6IFw3RSoWPfosh4PfHsbZByGpj2h7WUlH6+ISDm3PTGFBRv3AdDzxKIn6XJEp8ZVee/Kjlz94Vx+WrqdWat3A3B+m1pBSVArxoTTq1UCExZuYdyfG4slST+QksYX8zbx8az1rNmVlLX+zGbVGdqlIWc2q05ISBArE8oIf5L0FCAKwLg2EhHA7caYuwo7X7m1dhqQ56dkrR2a6/mzwLOFjFdE5PhjLXx/N6ybARGxMGgsVCglU6qEhsGlo+CD82DHUvj0Mrh6EkTlGhznz/dhwywXf9+XgtsCQESknMqcG/2k+pWoEe/fwF2St9NPqMbbV5zC9R//yYHDrqn3gI71ghbPZR3qMWHhFr5ZsIVrT29M9bhIYiJCi9z0fdWOg3w0ax3j520iKdWlhLGRYfQ/pS5Xdm5A4+qxgQi/3PAnSV8J3GGMeRYYBCTi+oVPNcZcaq3dHsgARUTEhzlvwV8fAgYueR9qtgx2RDlFxcPgcfDe2bBjCXwxzN1ICPX+2dm3EX5+2D0++yGoFLx/WEREyrOfvEn6uS0TghzJ8eusFjV4bfDJ3DL6L06oEcepjaoELZYuTapSp1I0m/cdovvz0wCICAuhaoUIKsdEUKXCkaVyTARVYiOoEhNB5QrhVK0QSeUK4VSOiSA8NIQMj+WX5Tv4cOY6flu1K+scTWvEclXnBvzr5LrElqGR+UsTf961+4ExwO1AOnATrnn6i8B8oHbAohMRkaP98zP86EZy59zHoHn+05UFTaV6MGgMjOwDq36GH+6B8729mr67C1IPun70Ha8NbpwiIuVUYkoas1a75CoQ/dElb+e1SuC3e3tQITKsxAeMyy4kxHBv7xY888Nydh08zOF0D6npHrbuT2Hr/pQCHyc+KozQEMPeZDfIYIiBs0+sydAuDenSpGpQX+PxoNBJurV2ojGmDtAM2Git3ebddLsxZmZAoxMRkZx2LHe10tYDJ10BnW8JdkT5q3MyXPIejL0C/vwAqjSB2Jrwz08QGgEXvgohx/covyIipdW0FTtJy7BZc5NL8apZSroTXNiuNhe2q421lkNpGexJSj1q2Zvsa10ae5NTsZasUdorxYQzoGM9rjitAfWqxAT5lR0//Gp/YK3dD8z1sX5skSMSERHfknbDZwPgcCI06Arnl5F+3Cf2hfOecLX/P93v+qADnDkCqjcLbmwiIuXYT0tcXdu5rdTUvTwyxhATEUZMRBh1Kxcswc7wWPYfSmNP0mEOpKTTIiGe6IjQYo60/PFnnvQz8tturZ3ufzgiIuJTeiqMGwJ710GlBnDZxxAWEeyoCq7TzbB7tRssLvUA1GwNXe8IdlQiIuXW4fQMpq3YCcC5LdXUXQomNMRk9VmX4uNPTfo0wDvT3VEjs1tAt1JERALJWvjuTlj/O0R6B2SrUDXYURWOMdD7WUjZB2tnwEWvQajmRxUpr5JT00n3WOKj9D0QLLNW7+bg4XRqxEXSrhjnyxaRwvMnSV8IVAPexw0YtyegEYmISE6zXof5n4AJgf4fQI0WwY7IP6FhLn5PBoTofq5IeeXxWC567Xf2Jqcy6Y4zqBYbGeyQyqXMUd17tqypeatFSplCj9ZjrT0J6AfUAf4A3gDaW2v3e/uqi4hIoKyY5PpxA5z3JJzQM7jxBIISdJFybfHm/fyz4yC7Dqby4cx1wQ6nXPJ4bNb86OqPLlL6+DWkrrV2rrX2OqARMBP4xhhzZ0AjExEp77bMdyO5Y+Hkq+C0G4MdkYhIkf26cmfW449mrSfpcHoQoymfFm7ax84Dh4mLDKNz4zLWfUqkHPB73htjTD3gHuA/wF/AjEAFJSJS7u3bAKMHQFoyNOkB579QNkZyFxE5hmkrdgDuK23/oTTGzN0Y5IjKn8ym7t1b1CAiTNNgipQ2hf6tNMZcbIz5HtfUPRroYa3tYa39M+DRiYiUR4f2waeXwsHtbhT0Sz/UIGsiclzYl5zKgo37ALj1rKYAvD9jDWkZniBGVf5kTb2mUd1FSiV/bp19CbQGxuMGnrvJGPNi5hLQ6EREypv0VBh7BexcDnG13UjuUfHBjkpEJCBm/LMLj4VmNWO5+aymVI+LZMv+FCYs2BLs0MqNVTsOsnpnEuGhhu7Nqwc7HBHxwZ8kfTqwGmgFnJRraR+wyEREyhtrYcKtsG4GRMTB5eOgYp1gRyUiEjCZ83J3b16DqPBQhnVtCMDb01djrc1nTwmUzAHjujSpRpymwBMplQo9BZu1tnsxxCEiIlOfhEVjwITCZaMgoU2wIxIRCRiPx2YNGndmM1eDe/lpDXhj6mpWbj/I1BU76NFCza+L209LvU3dW+m9FimtijJwXFNjzHnGmGjvc41oJCLir78+hunPuscXvAxNzwlqOCIigbZ0ayK7Dh4mJiKUDg0rA1AxOpzLT6sPwFvT1gQzvHJhR2IK8zfsA6DniUrSRUorfwaOq2qMmQKsBL4Hank3vWeMeSGQwYmIlAurpsDEO9zjbnfDyVcGNRwRkeKQWYvepUk1IsNCs9YP69qI8FDDH+v2MG/93mCFVy5MXuaaurevV4ka8VFBjkZE8uJPTfpLQBpQH0jOtn4s0CsQQYmIlBvbFsO4q8CTDm0ugx73BzsiEZFi8au3P/qZuQYrS6gYxb9OcuNvvP3r6hKPqzz5aYlL0tXUXaR08ydJPxe411q7Kdf6f4AGRQ9JRKSc2L8ZPr0MUg9Aw25w0WuaC11Ejkv7D6Uxb4OrJe/e7OgRxa8/ownGuJreVTsOlnR4RTZz1S7W704Kdhj5OpCSxszVuwA4t2VCkKMRkfz4k6RXIGcNeqZqwOGihSMiUk6kJMLoy+DAFqjWHAZ8DGGRwY5KRKRYzFy1iwyPpXH1CtSrEnPU9qY1Yul5Yk2shXeml63a9NlrdjP4vTlc+tYsDh5OD3Y4eZq2YidpGe4zaFojNtjhiEg+/J2CLXuHSWuMCQHuAaYGJCoRkeNZRhp8fhVs/xsq1IDLP4foysGOSkSk2GRNvdasRp5lbjizCQBfzd/Mtv0pJRJXILw3Yy0AOw4c5q1ppfcGw0/eqddUiy5S+vmTpN8D3GCM+QGIAJ4F/gbOAO4NYGwiIscfa2HinbD6FwiPgcFjobJ6ConI8cvaI1OvdW9+dFP3TKc0qMypDauQlmEZ+fvakgqvSNbvTmLK8u1Zz9+dsYbN+w4FMSLfDqdnMHX5DkD90UXKgkIn6dbapUBb4A9gMq75+5fASdba0nv7UESkNJjxPMz/GEwI9P8A6pwc7IhERIrViu0H2JaYQlR4CKc2qpJv2Ru7Nwbg0zkb2H8orSTCK5JRM9dhrZv3vVPjKhxO9/DMD8uDHdZRZq/Zw8HD6VSPi6R93UrBDkdEjsGvedKttdustQ9Za/taa/tYa++31m4NdHAiIseVRePgl8fd497PQvPewY1HRKQEZDZ179y4KlHhofmW7d6sBs1qxnLwcDqfzllfEuH9f3t3HR7HdTVw+HcXxGRZYEmWjDKDzBA7hsQO2eGGuQ1j2zRN2pTSNmnztWkacMPMnNhBxzHGTDKDwBZYLItpYb4/ZleWHUkWLMrnfR49Wu3MzlxJY3nP3HPP6bLqBgsfbtbrKN80YwAPnzcCpeCL9CNszfGtVnLf7S4EYN6IeAwGKVAqhK/rUpCulOqllLpfKfWyUuolpdSvlVLt3xoVQohTWfZq+OwO/fG0u2Dyzd4djxBCeMiK/Xqa9eyhba9HdzIYFLeerq9Nf/XHQzRYbG4dW3d8tCWPmkYrg2JDOT01hlFJkVw6vi8Af1uyB03TvDxCnd2usbR5PbqkugvhDzodpCulZgHZwD1ALyDa8TjbsU0IIURLJfvh/avBboERF8C8v3p7REII4RE1jVY2H9JnlWe10nqtNeenJZIYGURJdSOfbst35/C6zG7XeH3tIQBuOG0AytE+8zdnDSUkwMjWnAoW7/CNJNP0vAqKqxsJCzQxbVBvbw9HCNEBXZlJfxb4ABigadrFmqZdDAwE3nNsE0II4VRdBG9dCg2V0HcyXPQ8GLqUxCREm8prm3jiu/0UVflPRWxxavgxoxSrXaN/7xD6x4R26DVmo4GbZgwA4IVVWdjsvjEj3dLy/cUcKqsjIsjEJeOTmp+PiwjidkeV+n9+vc8nMgGcVd1nD40l0NT+cgMhhG/oyjvFQcC/NU1r/qvjePyEY5sQQgiAplq9F3plDkQPhCvfA3Owt0cleqB/fr2Pp37I4MGPd3h7KEIcx1nVvaOz6E5XTk4hMthMdmlt83pqX/KKo/r8FZNTCAkwHbft5tMHkhgZRH5FPS+v8X6VeufPb/5Iab0mhL/oSpC+FRjeyvPDge3dGo0QQvQUNit89HMo2A7B0XD1RxAqaYbC9eqbbHy5U0+rXb6/hB15Fd4dkBAOmqax0tkfvQPr0VsKDTRx3TS9PeVzKzN9Zn03wP7Can7MKMOgaB5jS0FmI789ZxgAi5ZnUFztvQyXjOIaMktqMRtVu+3vhBC+pStB+lPAfx2F42Y4Pu4H/gM8qZQa4/xw7VCFEMJPaBp8/Rs48DUYA/UZ9N6SaCTc49vdhdQ0Wpu/fvqHDC+ORohjMopryK+oJ8BkYOrAzt+kvH56fwJNBtLzKlmfVe6GEXbNa2v12fGzRvahb6+QVvc5f2wiaclR1DbZ+Pe3Bzw5vOM4C8ZNGxRDRJDZa+MQQnROV4L0d4Fk4HFglePjcaCfY9s29Bn1ba4ZohBC+Jk1/4HNrwAKLnkRUqZ4e0TCTTYfKmdjtneDh4+36i2gzh+biFL6m/I9R6q8OiYh4Fiq+5QB0QQHdH4tdExYID+bqFdLf25lpkvH1lVHa5v4ZKtezO7G0wa0uZ9Sij8s0BNPP9iS67V/k9/tcaS6S1V3IfxKV4L0ASf5GNjisxBCnFp2fAjL/qI/PvsxvZq76JHKahq56qUNXPXievKO1nllDEcq6lmTUQroVaXPG50AwDPLD3plPMJ3NVptZJfWsjXnKBab3SPnXNHFVPeWbpk5CIPSA35fuPn07qYcGq12RiZGMKl/r3b3ndAvmgVjEtA0+NuXnm/JVlzVwLacCkDvjy6E8B+mk+9yPE3TDrtjIEII4feyV8Fnt+uPp94JU2/37niEW329q5Amqx7svLcxl/vPGurxMXy6LR9N02cqk6NDuHtuKkt2FPDVzkIOFFUzJD7c42MS3mG12SmobCD3aB155fXkHa0j96jjc3k9RdUNOGPEn88YwB8WjHDreGobrc1ZJt1ZC53SO4RzRyewZEcBL6zK5MkrxrlqiJ1msdl5Y63+NvjGFm3X2vPgOcP4bk8RazPL+H5vsUeD5aV79VT3tOQo4iOCPHZeIUT3dTpIV0r11jStzPE4GbgZCAa+0DRttYvHJ4QQ/qFoD7x3zbFe6PP/5u0RCTdbsuNI8+P3NuVyzxmpBJg8115P07TmVPdLJugpwUP7hHPOqD58vauQZ37I4KkrvRfQdMf6rDLe3pCD1WZvDiw1NDQNnHOR+vNai+36z6Tl9iCzgV/OG8KwPhEeHb+7FFTWk1teT255HXlH6/WA3BGEF1Y1nLRVWZDZQIPFzpvrD3PrrIHEhbsvcFufVUaTzU7fXsEM7GDrtbbcNmsQS3YUsHhHAb+eP5Tk6NbXgbvbN7sKKaxqICYsgIVjEzr0mr69QvjFjAEsWpHJo1/tZdaQWI/9nfhutx6kzx8ps+hC+JsOB+lKqdHAYiBZKXUQuAL4BggF7MAvlVKXapr2mTsGKoQQPquqAN7+GTRWQvJUuOgF6YXewxVXN7DBMUsYGWymtKaR7/YUsmBMosfGsD23gqySWoLNRs4dfSxguGvuYL7eVcjiHUe454xUBseFeWxMrvLI4j3sKXBNarNBKf53zQSXHMub/rpkz0nbeQUYDfTtFUzf6BD69gomuZfjs+Pr3qEBXPK/tWzNqeDl1dk8dG5rzXpc41iqe2yHZpzbMyopkhmDY1iTUcrLa7L58/kjXTHETnvV0Xbt6in9OtVv/I45g/lgcy7ZpbW8uf4wP5/R9lp2V6lusLA2U18KM3+EtF4Twt90Zib9cWAncI3jYwnwFfALx/angQeBz1w4PiGE8G0NVXqAXpUHvVPhynfB3PPSChutNp5adpDQQBN3zB7s7eF43dc7C9E0PY309NQYnvohg7fX53g0SP9oiz6LfvaoPoQFHvvvfGRiJGcOj+f7vUUsWp7BE5eneWxMrlDbaGVfoR6g//7c4QSZDaAUzjBPKVAox+fjn3M+oYCSmkYe/2Y/qw+WYrHZMRv998ZZdYOFtzfoadZ9ewWTEh3ykwA8OTqE2LBADIb2A+K75g7mptc289b6w9w+exBRIQEuH6+maaw4UAzArCFdX4/e0m2zBrEmo5T3NuVwzxmpRIe6ftztSc+tYGtOBWaj4uqpKZ16bVigiV/PH8pDn+zkv98f4OJxSfRy8/hX7C/BYtMYGBvqlzfqhDjVdSZInwTM1TRth1JqO3ALsEjTNDuAUuppYL3rhyiEED7KZoEProOinRAaB9d8BCHR3h6VyxVXNXDrW1uaCxBdkJZEUlSwdwflZc5U9wVjEjh3dALPLM9gXVYZGcU1HnlD3GCxsThdH8OljlT3lu45YzDf7y3i83R9Nr1/N9ONPWlHXiV2DRIjg7j59K7XoLXbNV5enU1ZbRObDx1l2qDOtwDzFV/vLKTBYmdgbCjLfjWrWzPTc4bGMSIhgj0FVbz64yF+OW+IC0eqyy6tJbe8ngCjgeku+rmfNrg3IxMj2H2kijfWHeK+M10/7vY4Z9EXjkns0jKByyYm8/raQ+wrrOa/yw66PRvgO0frNZlFF8I/dea2cjRQCKBpWg1QC7TsO3MUkAo1QojO0TQoPQhb34TP7oQX5sBrC/Tgd/G98P1fYO3TsO1t2PcV5KyHkgNQWwo268mP785xL74XspaDOQSueh969ffeeNwkPbeChc+saQ7QAdZnlnlvQD6goLKeTYeOAnDu6AQSo4KZO0xf8/nOhhyPjGHZ3mKqGqwkRgYxrZX+02P6RjF7aCw2u8aiFf7VN31rjv6zHZfSfuXskzEYFLMcBctW7C/u9ri86SNn7YHxfbudOq6U4s45ejbMa2sPUdPo+r+jzlT3SQN6ERrY6fJHrVJKcdusQQC8vvYQdU2e+/tfVNXAlzsLgPbbrrXHaFDNxfreXH+YjOIal43vRE1WOyv26de8rEcXwj919i/niRVJPNtLQgjh/6xNUJAOOesgd4MedNeVdv14gZEQ0guCe0FwtD6THdIbUufBoDP0PFh3WPEYbH8blAF+9hokjXfPebzo0215/PbjnTRZ7QyOC2N4QgSL04+wPqusuVDZqejLHfqb9Yn9epHoyCi4ZmoK3+8t4qMtufzmrKFd6gndGR9tyQXgovFJbaY33z03lRX7S/hkaz53z031WrGtznLeEBqXEtXtY80ZGscnW/NZvr/Yreuv3Sm3vI6N2eUoBRePT3LJMc8e1YeBsaFkldTy1vrDzcGvqzj7o88a0vWq7q05Z1QfUqJDyCmv44NNudzQxYC5s95afxiLTWNiv16M7hvZ5eOcNjiGM4fH8f3eYh77ai8v3zDJhaM8Zn1WGdWNVmLDA0nrG+WWcwgh3KuzQfprSqlGx+Mg4DmlVK3j60DXDUsI0WPUV0DeJj0oz1kP+VvA2nD8PsZASJoAKVMgcZweyNcfhfpyqCs/4bHj64ZK/bWNlfrH0UPHH3PDc9BvBpz5J0ie7NrvaesbsPKf+uPznoAhZ7n2+F5ms2s8/s0+nl+VBcCZw+P4z+VpbDl8VA/Ss0/tmXTnjNqCMceKtZ2eGktydDC55fUs2XGEn01Mdtv5i6sbWHVQv7F1yfi2b5ZM6NerudjW/1Zm8uhFo902JlfRNI3tua6ZSQf992I0KA4U1ZB3tI6+vfzjRkVLzgr+pw2KISHSNctMjAbFHbMHc/+H6by0OpsbpvcnyOyaG0sNFhvrs/S/Ed3pj94ak9HAzTMH8IfPd/Pi6myumdoPk5trDTRYbM0ZMje5oODb784dzor9JSzbV8yag6XMSI3p9jFP9N2eQkDvjX6yGgVCCN/UmSD99RO+fquVfd7oxliEEP5O06AyVw/GnR/Fe/hJ0k1wNKRM04PylGmQMBZMnbzPZ7NCQ0UrQfxRKDsI29+Fw2vg5Xkw9FyY+weId0Ff4IPfw+L79Mcz74eJN3b/mD6kst7Cve9ta05XvXPOIH49bygGg2Ji/2iMBkWuowezPwY83ZV3tI5tORUoxXEV1Q0GxVWT+/HPb/bx1oYctwbpn287gs2uMT4lioGx7a9/v+eMVNZklPLh5lzumjO4eebfV+Udrae0pgmzUTEysftt0yJDzExI6cXGQ+Us31/CtVP7uWCUnmO3H2uz11rtge64IC2RJ78/QN7Ret7flMv10/u75LjrsspotNpJjAwi1Q31GX42MZknvz9IfkU9X+4s4II012QXtOWL9COU1TaRFBXMfBf0OB8YG8a10/rx6o+H+NuXe/jynpkYXRhI2+0aS5vXo0uquxD+qsNBuqZpPeudqBDCNerKIfMHOLgUDq2Gqvyf7hM9CFKm6h/JUyEmtftp6EYThMboH62ZeT+s/Adsfwf2fwX7v4Yxl8Och7q+drwgHT68HjQbjLkC5j7c5eH7osySGm5+YzNZJbUEmQ08fulYzh97rFp5WKCJMX0j2ZZTwfqsci6dcOoF6c5U9ykDoomLOL541M8m9uWJpftJz61gV34lo5K6nhbbFk3Tmqu6d2TJweQB0UwZEM2G7HKeX5nJXy4Y5fIxuZJzPfqIxEiXzezOHhbLxkPlrNhX7HdB+qZD5eSW1xMWaOKska4tAGY2Grh11iD+8Nkunl+ZyZWTU1zSv3ul4wbfLBe0XmtNkNnIDdP78++lB3huZRbnj010y3lA//f26o+HALh2mutm7e89I5VPtuazr7Ca9zflctWUzlWLb8+O/EqKqhoJCzT5dbFEIU51/tuPRAjhHXa7nrK+4p/w0pnwf4Pg45/Djvf0AN1g0lPXp90Fl70J9x+Ee7bChYtg/HUQO8R968RbikqGC56FO9bD8PMBTR/j0xPhqwegppOFpCpy9FZrTTUwYBac/7Rnvg8PWb6/mAuf/ZGskloSIoP46LbpxwXoTlMdRcqc6aynmiU7nKnuP/3ZxIQFcs4ofXbd2S7L1XYfqWJ/UTUBJkOH273de0YqAO9uyqW4quEke3uXcz36eBesR3ea40i5/jGzlAaLzWXH9QTnLPq5o/u4pc7Bzyb0JS48kCOVDXy2rZUbrF1wbD26a1PdW7p2Wj9CAozsLahqPp87bMguZ29BFUFmA1dMcl12TFRIQPO/yyeW7qe6weKS42aV1PDMDwcBvT99Z3q5CyF8iwTpQoiTqyuHnR/BJ7fAv1Lhxbmw4lF9rblmh7iRcNq9cN0X8GAu3PwDnPV3GHE+hLnvjVqHxA6Fy9/UxzRwNtgtsPF5+G8a/PC3Y2vb21N/FN66FGqK9O/18jfB5Nkeve6iaRrPr8zk569torrBysR+vfjirhltzgKfykH6odJaduZXYlB64a3WXOOYqf1s2xGqXPTGuyXnLPr8EfFEBps79Jppg3ozoV8vmqz25joDvmqbiyq7tzSsTzh9IoJosNjZkF1+8hf4iPomG1/t1NcWt1d7oDuCzEZunqm3uVu0IgObvXv1gA+X1ZJdWovJoDhtsPtmcaNCArhikj77/PxK913Tr6zR265dPL6vy/vJXzutHwNjQimtaeLZ5ZldPk6j1cbn2/O54oV1zP33Sr7fq9+Adtc1I4TwDAnShRA/1eZs+ft6JfaAcBi+EBY+Bb/cA3eshXmPwMBZEOCjKdBJE+C6z/WPxPFgqYVV/wf/HQs/PgWW+tZfZ22E966B0v0QnghXfwhBrk9j9oYGi41ffZDOY1/vw67B5ROTefvmKcSGt10fYGK/XpgMiryj9eSW13lwtN7nLBg3fVAMMWGt/4wm9e/FkPgw6i02l81MOjVZ7Xzh6I3emer6Sinucczavb3hMKU1jSd5hXc0WGzsPlIFwLjkKJcdVynFnGF6lfHl+/ynFdu3uwupabSSHB3MpP7RbjvPVVNSiAoxc6isjiU7jnTrWM5Z7Qn9ehEe1LGbSF31i5kDMBkU67LKWJzevXG3Jre8jqV79bXdN7povX5LZqOB3zk6DryyJrvTf08zimv425I9TH10Gfe+t531WeUYFMwdFserN05izjAv3yAXQnSLBOlCCAACrNWoXR2YLb9+CTyQBZe/BROuh0j3Fu1xuYGz9Vn1y9+CmKH6LPnSP8BT42HLa8f3Xrfb4bPb9QJ0gRFwzUf+9/22obCygcufX8en2/IxGhR/XjiCf1wy+qTpkaGOdelw6s2mH0t1T2hzH6UUV0/RZ9PfWn8YTXNdp9Ll+4spr20iNjyQmYM7VxH69NQYxiZH0WCx8+Jq35xN332kEqtdIyYskL69XFvgzlll3J/6pTtT3S8e19etFbpDA03c5Ghltmh5JvZuzKY7C066uqp7axKjgrlisp6Cfve723hq2UGX/nt7fe0hNA1mpsaQGh/usuO2dMbwOE4b3Jsmm51/fLPvpPs3OG7+Xfb8Os58YiUvrcnmaJ2FhMgg7jszlTW/ncsrN0xqXuIhhPBfEqQLcSqz22DP5xjfXMjZO+/C9PltJ58tHzDT/1O9ldK/tzvWwQWLIDIZqo/A4nth0RTY9YkeoC/7M+z6GAxmPcU9fqS3R+4SW3OOcv4za0jPqyQqxMwbN03mhtMGdLj40rGUd/9JHe6uzJIa9hZUYTKoNlPdnS4an0Sw2ciBoho2HTrqsjF8vMUZtCV1uoCVUop75g4G4M11hymvbXLZuFxl6+EKQF+P7upCYKcNjsFsVBwqqyOrpMalx3aHgsp61mScvM2eq1w/rT9hgSb2F1XzvWP2uLMaLDbWZeo37lzdH70tf144khtP6w/AE0sPcPe726hv6n7dgdpGK+9vzgVovoHhDkopHj5vBErpRSk3H2r9b+rBomoeWbyHKY8u4773t7MxW581P3N4PK/cMJE1v53LfWcO8fnuDUKIjutsn3QhRE/QUAlb39TXZlfkNN+t0+JGolLnQeo8SJ4CRvemK3qdwQjjrobRl8LmV/T097IM+OhG6PUIHNXXI3LBM/oMfA/w0ZY8fvfJTppsdobEh/HSdZNI6d25JQpTB/Zm0YrMU2omfUm6Pos+IzXmpGtTI4LMXJCWyHubcnl7w2EmD+h+qnJZTSM/OFK1O5Pq3tLcYXGMTIxg95EqXlmTzf1nDe32uFxpmwv7o58oLNDElAG9WZNRyvL9JSdtXedtn27LR9Ngcv/oTv/77IrIEDPXTuvH/1Zk8uzyDOaNiO/0jZJNh8qpt9iIjwhkeIJ7Zp5PZDIa+NPCkQyJD+cPn+1iyY4CDpfV8eJ1E+kTGXTyA7Th4615VDdYGRgT6vYbDsMTIrh8YjLvbcrlr0v28Okdp2EwKBosNr7cUcC7G3PYfPjYzb6kqGAun5TMzyb2JSFSgnIheiqZSRfiVFKeDV8/CE+MhO9+r1csD47Gdtqv+G7kE1hvXgnz/gL9Z/T8AL0lUyBMvR3uTYfZv9OzCJwB+tyHYewV3h2fC1htdv66ZA/3f5hOk83OvBHxfHLHaV0KACY41qXnV5w669Kda3XPG912qntLzpT3r3cWUuaCNeBfpB/BatcYnRTJkC6m3iqluHuuvjb9tbWHqKxzfWG77nBWdh/nwsruLc0eqgdbvp7yfnybPc8tr/n5jAEEmQ2k51U2z+J3hjPVfdYQ97Rea8+Vk1N46xdT6BViZmd+Jec/s4btuRVdOpbdfqzt2vXT+7t1qYHTr+YPITTASHpeJYtWZPDnL3Yz+e/f8+sP09l8+ChGg+KskfG8duMkVj0wh3vOSJUAXYgeToJ0IXo6TYPDa+G9q+Hp8bDhf9BUra/HXvAk/HI39tm/oz6gc2tce6TAcJj9Wz1Yn/VbOOtRvd+6n2uy2rnp9c287KhUfM/cwTx/zQTCAruWTBUaaGKso7DXulNgNn1/YTUHi2sIMBqY38Fe1aP7RjK2byRNNjsfOgKu7nCuT760i7PoTvNHxDOsTzg1jVZeXZvd7XG5SkFlPQWVDRgUzTUPXM1ZSGtDVjm1jdaT7O0923MryCqpJchs4NwO3hRyhZiwwOaK6c/8kNHp13ui9Vp7pg7szRd3zWBIfBjF1Y1c/vw6Pt/e+eKNKw+UkF1aS3igqctZK50VFx7EHXP05Sj/+u4Ar609RFWDlb69gvnNWUNZ9+Bcnr92IrOHxmH0wE0DIYT3SZAuRE9lbYIdH8ALs+HVc2DfEr0A3KAz4JqP4c4NMPFG363G7k2hvWHO72DanT2iF/rSPUWsOlBCkNnAs1eN51fzh3Z7dmjqQD2F+1RIef/SMYt++pCYDrc9A7ja0Y7tnQ053SrGtb+wml35VZiNqtXe9Z1hMBybTX9lTbZb2sR1hXMWfVifCEIC3LMSb2BMKCnRITTZ7KzN9N3r1nlD5uyRfdxeIf1Et84aiNmo2JBd3ub66NbkHa0jo7gGo0ExI9V7N3yTo0P4+PbpnDEsjkarnXvf286/vt3fqX9/r/yo37y6fFJyl29kdsXPZwwgNS4Mk0Fxzqg+vHHTZFb9Zg53zhlMXETXU/eFEP5JgnQhepq6clj9b/jvGPjkZijYDqYgGH893LEBrv0EBp/ZI4JP0THO3tOXTUzmvHYqk3eGs3jchqxyl1ZU9jWaprWo6t65AHnhmEQigkzklNex6mBJl8fgDNrmDoujV2j3izaeM6oPg+PCqGqw8sbaQ90+nis4r9Hx/aLcdg6lFHMcKe/LfTTlvdFqY7Gj/oGnZnFbSogMbs7WeGZ5x2fTnbPo45KjOnUjyx3Cg8y8cN1Ebps1CNC/j9vf3tKh7ImM4mpWHyzFoPRUd08KMhtZfPcMtv1xHv+7ZgKnD4n1SKq9EMI3SZAuRE9RcgAW3wdPjIBlj0B1AYTFw5yH4Ze74fynIG6Yt0cpvCA9rwKAMX2jXHbMluvS84620WO+B9hTUEVWaS0BJgNnjojv1GuDA4zNgdbbG3K6dH6rzc4nW/WUXVdV+dZn0/XU2pfWZFPjA6nfzevRk11fNK6l2Y6U9xX7in3y5tKyvcVU1lvoExHE9EHemZG+bdYgDEpfY74rv7JDrznWes0zVd1PxmhQPHjOMJ64bCwBRgPf7i7i0ufWkXe0/RoazrXoZw6PJzna81lmQWajx7MnhBC+SYJ0IfxZYw0cXApvXQrPToItr4K1HvqMhgufg/t2wqzfQKisNz9VWW12duVXAZCW7Lq1viEBLdal+3DqcHc5Z9HnDI3tUuqrs4Dcsr1FHKno/M2M1QdLKa1ppHdoQPOaaldYMCaRATGhVNRZeGv9YZcdtyuarHZ2OoJBdxWNc5o2sDdBZgNHKhvYX1Tt1nN1hbPN3kXjk7y29rhf79DmZRXPdmA2vclqZ62j0Jwn+qN3xsXj+/LuLVOJCQtkb0EVFz77I1sOt57GX1HX1HxD7EY3tl0TQoiOkCBdCH9hs0BBOmx+FT6/CxZNh38kw9uXQsZSQMHQ8+CGL+HW1ZB2pV61XJzSDhbXUG+xERZoYmCMa9tOTWvul94zg3Q91V1fj97ZVHenwXFhTB0YjV2D9zbldvr1HzlS3c9PS8Tcyd7o7TEaFHc6ClW9uCrLJb2lu2pvQRWNVjtRIWYGxIS69VxBZmPzDPXyfV1fguAOJdWNrHCkjXuiN3p7nEXMvtldSEZx+zczNh8up7bJRkxYACMSIjwxvE6Z0K8Xn991GiMSIiitaeLKFzbw4eaf/lt8b1Mu9RYbw/qEN9fcEEIIb5EgXQhfpGlQngU7P4JvHoKX58NjfeH502HJfbDtTSjerReCC0+EybfC3Vvgynf09mmy3lw4pDvaEI1OinT5+sapLYJ0X0wd7q6d+ZXkltcTbDZyxvCuzxBe4ygg997GHCw2e4dfV1lnYenuIsA9QdsFaYkkRwdTVtvE2xu8N5vuXI8+LjnKI627fHVd+ufb87HZNcYmRzE4zrt93IfEh3PWyHg0DRYtz2x335WOVHdfXkOdFBXMR7dP4+yRfWiy2fnNRzt49Ku92BwF5aw2e3N9hptOG+DxFnJCCHEiz5WtFEK0raYY8rdC/hb948hWqD/60/0CIyFpHCRN0D8Sx0OE51r0CP+TnqenEY9xYaq70/h+UZiNiiOVDeSW13ep57ovc6a6zx0e162K4/NH9CEmLJDi6ka+31PEOR1sq7V4xxGabHaG9QlnZKLrZyjNRgN3zh7Mg5/s5PlVWVwztR9BZqPLz3My2xw3ksaluHc9upOekr2bLYePUllv8XqhM6ePHanWl473XG/09tw1J5VvdxfxefoR7jtzSJv/vo+tR/etVPcThQSYWHT1eJ78/gBP/ZDBC6uyOFhUzVNXjmP1wVKOVDYQHRrA+Wnd66AghBCuIEG6EN5SlgnL/w65m6CylaJSxkB9bbkzIE+aANEDwSAJMKLjnDPpaS4sGucUEmBibN8oNh8+yvqssh4VpGuaxpeOIH1hNyviB5gMXD6pL88uz+TtDTkdDtJb9kZ318zexeP78vQPGeRX1PP+plyPV7SGFkXj3Lwe3Sk5OoTBcWFkFNew5mCpyzoedMfuI5XsLagiwGhgYTfb7LnK6L6RnD4kllUHSvjfykweu3j0T/YpqKxnf1E1BgUzB/t+7RODQfGr+UNJjQ/n/g/TWb6/hIsXrSXApP+/evWUFK/cqBJCiBPJu30hvKGpDt65HHZ97AjQFcQOg7Sr4bx/wy0r4KE8uHkZnPs4jL0cYgZLgC46pcFiay6O5Szy5mrTBukp7+t62Lr0rTkV5FfUExpgdMkM4ZWTU1AK1mSUkl1ae9L9M0tq2JZTgdGguCDNfTOrASYDt83WW1X9b0UmjVbPrk0vrWkkp7wOpdx3jbbG11LeP96iz6KfOSKOqJDut9lzlbsca9M/3pJHYWXDT7Y7U93HJke5pD2gpywcm8iHt00jPiKQg8U17D5ShcmgmpemCCGEt8k7fiG8YekfoewghCfAdV/Agzlw5wa4cBFM+gUkjgOT/7zhEb5p95FKbHaNmLBAEiKD3HKOnrou3Vkw7swR8S6ZWevbK4Q5jmD/nQ6s/3ZW+Z41JJbYcPcWgLxsYl/6RARRWNXAR47zeopzFj01LowID7aecv4uVuwvxm737nVrsdn5fLtr2+y5yuQB0UzuH02Tzc4Lq7J+st3ZH33WEN9ovdYZY/pG8cVdMxjbV18KdEFaEvER7vk7KYQQnSVBuhCedvB72PSi/vjCRTBwFgT5XkVc4f+25+rr0dOSI92WLj0+pRdmo6KgsoGc8vZ7EPsLu13jq516qntXq7q35pqpKQB8uCWPBkvbM9Y2u8an2xzrkye4P2gLNBm5ddZAQC8S1pnidt11rGicZ9ajO03sH01YoInSmiZ2HelYL3B3Wbm/hLLaJmLCAjjdB4PdO+fqs+nvbDxMWU1j8/MWm501B32z9VpHxUcE8f6t03j9psk8evEobw9HCCGaSZAuhCfVlsHnd+iPJ98Kg+Z6dzyiR9uRVwHoM0buEhxgJM2RptxTWrFtPnyUoqpGwoNMnD7EdetsZw2JIykqmIo6S/N699asyyyjoLKByGBzt6rKd8aVk1OICQskv6KeTx0FzDzB0+vRnQJMBmYM9o1WbM7aAxekJbm0zZ6rnJ4aw+ikSBosdl75Mbv5+a2Hj1LdaCU6NIAxSa4vTOkpQWYjs4bEEmiStehCCN/he/8bCNFTaRosuRdqiiBmKMz7i7dHJHo4Z9E4d6/1dfZLX5fZM4J0Z6r7/BF9XPrG3WhQXDVFn01vr+XZR1v0Hs4LxyZ4LHAIMhu5zTGb/uLqLI8sXbDZNdIdN5I8Vdm9pTnDvL8uvaKuiWV79fP7Wqq7k1KKOx1r099Ye5jKegtwLNV9ZmqMz7ZeE0IIfyVBuhCekv4u7F0MBhNc/AKYg709ItGDVdQ1cahMTz93rrl0l2Pr0sv9fl26za7x1c5CABaMdX3V78smJmMyKLbmVLDnSNVPtlc3WPhmt37+Sycku/z87Y5tUjIBRgMHi2uaCw660/7CauqabIQFmrzSF9yZop2eV3FcGrcnLU7X2+wNT4hghBva7LnK/BHxDIkPo7rRypvrDgEtW6/5Xoq+EEL4OwnShfCEo4fgqwf0x3N+B4lp3hyNOAXscPRH79c7xO3Vosel9CLAaKCwqoHDZf69Ln1DVhmlNY1EBps5bZDrW0rFhgdy1qg+QOuz6V/vLKTBYmdQbKjbb66cKCLI3BxwLU4/4vbzbcvV16OnJUdh9MJMbHxEECMSItA0WHXQOynvH211Fozzjd7obTEYFHfM1mfTX16TzaHSWvYU6DeZZqZKkC6EEK4mQboQ7ma3wae3Q1M1JE+F0+7z9ojEKaA51d2N69GdetK69CWOgnFnj+zT3DvZ1a6Zord5+mxbPjWN1uO2OaurX+LG3ujtcfboXpxe4PasCG+tR2+pOeXdC+vSM4qrSc+twGRQXDjOt4N0gAVjEkiJDuFonYV73tsGwJi+kcSEubf7gBBCnIokSBfC3dY+BTlrISAMLn4eDFKcRrhfumMmfYyHZmOn9oB+6VabnW92uS/V3WnqwGgGxYZS22RrruIOkFNWx8ZD5SgFF3kpaDtjeBzBZiM55XXN2Rju0lzZ3ZtBuiPlfeWBEqwerGoP8JGjN/rsobF+EeiajAZunz0IOJapM9sHq9ELIURPIEG6EO5UkA4//F1/fM4/oVd/rw5HnBo07VhBrjQ3F41zmjowGvDvfulrM8sor22id2hAczE8d1BKcbVjNv3t9Yebf17OKt8zBseQEOmdmhUhAabmivLOAnruUFHXRGZJLQBpHm6/1lJachSRwWYq6y1sd2SfeILeZs+RNeGjBeNac/H4JBIij/USnyXr0YUQwi28GqQrpU5XSi1WSh1RSmlKqQs78JpZSqktSqkGpVSWUuo2DwxViM6zNMAnt4DdAsMWQNrV3h6ROEUUVjVQUt2I0aAYmeiZmfTxjnXpRVWNzQXr/I0zKD17VB9Mbm6Fdcn4vgSZDewrrGZrzlHsdq05SPdEb/T2OFPel+wowG53zw0XZ0A8ICaU6FD31kxoj8loaO5N7skq7z9mlFJUpdc+mOuhNnuuEGgycsvpeheAyGCzR5bTCCHEqcjbM+mhQDpwV0d2VkoNAL4CVgPjgEeBp5RSl7hthEJ01bK/QMk+CI2Dhf8FL6wvFacm53r0IfHhBAd4roVXmiNt2R/XpTdZj6W6nzfGfanuTpEhZhaO0YPht9fnsPFQOXlH6wkLNDF/RB+3n789s4bEEh5ooqCygS2OlHRXa16P7qFMj/bM9cK6dOcNmfPHJvpdf+6rpqRw88wB/POS0W6/mSWEEKcqr/511TTta03THtY07ZMOvuQ2IEfTtPs0TduradpLwCvA/e4bpRBdkLkc1i/SH1/wLIS6vkq0EG1xrkdPS/ZsdfCpftwv/ceMUqoarMSGBzJlgPtS3Vu6Zqqe8r5kZwEvrc4G9OJcnrqx0pYgs5H5I/UbBe6q8r7NcSPJm+vRnU5PjUUp2FNQRWFlg9vPV91g4VtHm71LvJw10RWBJiO/P28EZ49y/80sIYQ4VZm8PYBOmgZ8d8Jz3wI/V0qZNU2znPgCpVQg0LIiSziAxWLBYvnJ7i7hPK67ji98XH0Fps9uRwG28TdgHzAHfPxakGu2Z9numP0cmRDu0d/p5H76TYH1WWU0NTW5tTq5q6/ZL7brM5tnj4jDbrNit7nksO0aHh/CyMRwdh+p5vu9RQBcMLaPT/w7PHdUHB9vzePLHQU8dFaqS2dM7XatuWjc6ETPXqOtiQg0MCYpkvS8Sn7YW8DP3BA4t7xeF+8oosFiZ2BMKCPiQ7z+/QvRGnlfIPyJv1yvnRmf8pUCP0opDbhI07TP2tnnAPCapmmPtnhuOvAjkKhpWkErr/kz8KcTn3/nnXcICQlxwciFON6E7EX0rVhPTWA8K4b+DZvR96v2ip7DrsFDm4w02BQPjLGSFOq5c1vs8OBGI1ZN8fs0K3HeqX3WaRY7PLxZ/5ndM9LKoAjPnXtdkeK9LH3mPCZQ4+FxNp9YGWOzwx+2GKm1Ku4YYWNopOveKxTWwWPpJswGjX9OtmH0ge/3m1zF13lGxkTb+flQ91Z5f2qXkcxqxYIUG/OSfOM9mBBCCPerq6vjqquuAojUNK2qvX39bSYd4MT/0VQbzzs9BjzR4utwIG/+/PlERLjnnZjFYmHp0qXMmzcPs9nslnMI36R2fYRp23o0ZSToyjc5K2m8t4fUIXLN9hyZJbU0rP+RILOBGy8+2+NrRj8o2sTGQ0cJShnDuZPcl8rrymv2+73FNGzYTnxEIHdeNg+DwXNR4+wmK0seX0VNo5WrThvMeXMGeezcJ7PBtof3N+dRGpzCL88d6bLjfrQ1H9J3k5YSzcLzJrnsuN2RnF/J189tILPWzJnz5xBgcu2/G+f1OmziDDLXrUcpeOCyOcdVShfCl8j7AuFP/OV6rapqNy4/jr8F6YXAiRV14gAr0OoiSE3TGoFG59fO9Euz2ez2X6InziF8SGUefPNbANSsBzD1n+LlAXWeXLP+b3dBDQCjEiMJDvJ8Fse0QTFsPHSUTYcruHb6ALefzxXX7Ne79areC8YkEhjo2UrjkWYzf1w4gq92FnDDaQN96t/fBeOSeH9zHt/uKeZvF41xWeC6I78agPH9evnM95uW0puYsABKa5pIz69m+mD31BFZsku/1mYMjiElJtwt5xDCleR9gfAnvn69dmZs/laWcx0w74Tn5gObW1uPLoTH2O3w6W3QWAlJE2Gm1DIU3rHD0R99rJeqZk8b5Cge5yf90uubbM3rwT1R1b01l01M5rUbJ3u1FVlrpgzoTWx4IJX1FtZkuK7yuXM9+jgv9kc/kcGgmDVEb4XmrlZsdg0+3aYX4vN2mz0hhBC+zdt90sOUUmlKqTTHUwMcX6c4tj+mlHqjxUueA/oppZ5QSg1XSt0E/Bz4l2dHLsQJ1i+CQ6vBHAIXvwBGf0tSET3Fdkdl9zF9PVvZ3SktOYoAk4GS6kaySmvdco7Kegtvrs/hYKXCYuve+uEV+4upa7KRFBXsE+3AfInRoDhvtH7jYnH6T0q+dElNo5UDRY6ZdB+o7N7S3GHOIN09rdiyqiCvosEn2uwJIYTwbd6eSZ8IbHN8gL52fBvwiOPrBCDFubOmadnAucBsYDvwB+AeTdM+9sxwhWhF0R69JzrAWY9Cb99ZU+pJOWV1bpuB6gxN0/hhXxHFVe5vpeRrmqx29h7R1zuleSngDDIbm4Mvd/RL1zSNX3+wnUe+3Mcze4xMemw5t765mXc25HCkor7Tx1uyQw8+F4xJcGs1en+1cKwepC/dU0SDpfsl73fkVmDXICkqmLgI31qPPSM1BqNBkVFcQ255ncuPv7FEf8t13mjvt9kTQgjh27zdJ32FpmmqlY8bHNtv0DRt9gmvWalp2nhN0wI1TRugadpz3hi7EABYG+GTm8HWBEPOhgk3eHtEXnPHO1u48dVNrDzgnlmojvp2dyE3vbaZS59bR3XDqbUKZl9hFU02O1EhZlKivde9wtkvfX1WucuP/e3uQr7fW4zJoAgzadQ22vh2dxG/+3Qn0//xA/P/s5K/f7mHHzNKabS2H1TWNlpZtk9PdV8wJtHlY+0JxiX3IikqmJpGKytccBPOl/qjnygy2MyEfnoKviu+15bqmqxsL9NvAvljb3QhhBCe5e2ZdCH82w9/g6JdEBID5z+NT/RO8oLSmkZ25eszuB9syvXqWN5znD+nvI4/fr7bq2PxtHRHADSmb5RXZ4WnOYL0dZmuXZde1WDhT1/ov9ObZ/bnrxNtfHLbFH41bwjjU6IwKDhQVMOLq7O5+qUNjHtkKb94fTNvrT/c6szosn3FNFjs9OsdwqgkD/Zd8yMGg2LBGNelvDevR0/xnfXoLc0Zqqe8/7DPtUH60j3FNNoVyb2CmdTfN793IYQQvkMWzgrRVYfWwNqn9cfnPwVhcd4djxdtzD42Y7p0TxGVdRYiQzxfXbO4qoFVjpl8g4JPt+Vz+pAYLhp3asxcpTvWo6d5aT2609jkKAJNBkprGsksqWVwXJhLjvvvb/dTVNVI/94h3DFrID8sPcjopEjG94/hnjNSqahrYvXBUlbsL2HlgRJKaxr5fm9Rc2G4QbGhzB4ax+yhsUzqH82SdL2I13mjJdW9PQvHJvL8qiyW7SuittFKaGDX3jpomsbWnArAN2fSAeYMi+Wf3+xjbWYZDRYbQebup6Xb7BofbMkH4KK0RLnWhBBCnJQE6UJ0RUOlXs0dDcZdC8PO8/aIvGpDi7XHTTY7i3cc4Zqp/Tw+js+252PX9IJUs4bE8Z/vD/CHz3YzISWalN7eS//2lJYz6d6kr0vvxbqsMtZnlbkkSN+Wc5Q31h8G4O8XjW41eIoKCWDh2EQWjk3EbtfYU1DFygMlrNhfzNacCjJLasksyeblNdkEm43NReck1b19IxMjGBATSnZpLd/vLeKCtKQuHSenvI7y2iYCjAZGJvpm5sLQ+HASIoMoqGxgXVZZ88x6VxVU1nPfe9vZeOgoBjQuHOedDgJCCCH8i6S7C9EZZZn67PlrC6AyF3r1h7Mf8/aovG6DYybduZ7z4615Hh+Dpml87JitunRCMnfNHczk/tHUNFq5+71t3a4C7utqGq1klOg90scke3cmHVquS+9+8TiLzc5Dn+xE0+DicUmc1oEe1gaDYlRSJHfOGcyHt01n6x/msejq8Vw2sS/xEYHUW2xY7RqpcWEMT5B+1e1RyjUp79scs+gjkyIINPlm4TSlFLMdgfmKbqa8f7OrkLOfXM2G7HJCA4xcm2onuVfPv1kohBCi+yRIF6I9Nisc+hG+exienghPj9cfF+4AUxBc9AIEntpv8I/WNrGvUG+p9PeLRmE0KLblVJDpCBg9ZVd+FfuLqgkwGThvTAJGg+I/V6QREWQiPbeCJ78/4NHxeNrOvEo0DRIjg4gL937VbGe/9PVZ5d1el/7qj9nsK6wmKsTM788b3qVjRAabOXd0Ao9fOpb1D53B1/fO5K8XjOR/10yQ9OMOWDhWzzZYeaCYyrquFWT0xf7orWnZiq0r126DxcbvP93JbW9tobLewti+kXx+xzTGx7iuPoMQQoieTYJ0IU7UUAm7PoaPb4Z/DYbXztVnz8sOgsEMA2fD2f+Eu7dAyhRvj9brNh7SZ9FT48IY1ieC01P1Wc6Pt3h2Nt05ez9/RDyRwfp6+KSoYP5xyRgAFq3IZG1mqUfH5EnpeRWAvh7cF4xNjmyxLr3rN2xyy+v4z9KDAPzu3OH0Dgvs9tiUUgxPiODaaf1dtl6+pxsSH87Q+HAsNo1v9xR26Ri+vh7dafqg3gQYDeSU15FVWtup1+4rrOL8Z9bw9oYcAG6dNZAPb5tOv1NguY0QQgjXkSBdCIDybFj/P3j9fHh8IHx0E+z8AOqPQnAvGHM5XPoqPJAJ130OU2+DyFOjGNnJbHC02ZoyMBo41l7o02352OyemTlqstr5fHv+ced3Ond0AldMSkbT4Ffvp3O0tskjY/K0HT4WpAeajM3LH9Z1sRWbpmn88fNd1FtsTBkQzc+kdZVXOXumL3YU3OuM+iYbewv0DhC+HqSHBpqa/54t72DKu6ZpvLHuEOc/8yMHimqIDQ/kzZ9P5qFzhhNgkrdaQgghOkf+5xCnJrsNcjbA0j/Bs1PgqTT45kHIXgl2K8QMgen3wI1fw/0ZcPELMOpiCPL+Wl9f41xzPGWAnt585vB4IoJMeuGlzO6vR+6I5fuLOVpnITY8kJmtrFf+48IRDIwNpbCqgQc+3uHStmC+Ij1Xr+w+xsuV3Vvq7rr0L3cWsHx/CQFGA3+/aLSkpXuZs8De2swyymoaO/XaXUcqsdo14sIDSYoKdsfwXMq5Ln15B/qll9c2cfMbW/jj57tpstqZMzSWb+6dyczUWHcPUwghRA8l1d3FqaOmBLJWQOYyOPgd1LUIHJQR+k2HIWfD0HOg9yCvDdOfVNZZ2Fuoz445Z56CzEYWjE3knQ05fLw1jxmpJy/y1V3O1PqLxiVhMv703mNIgImnrhjHxYvWsnRPEW9vyPFK9Xl3KaluJL+iHqVgdJLvBekbsvR+6Z0JsivrLfxl8R4Abp89SNLSfUD/mFBGJ0WyM7+Sr3cVdurf0LH+6FF+cbNlztBY/rpEby9Z02glrI22c2szS/nl+9spqmokwGjgwXOGceNp/f3iexRCCOG7JEgXPZe1CXI36EF55g9QkH789sBISD0Thpyjfw727WJGvmjToXI0DQbGhB5XrOyS8X15Z0MO3+wq5K8Xtv0G1xXKa5uaZ7suGd92OvSopEgeOHsof/tyL39dsofJA6IZEt8ziv45U90HxYYRHuT5/vRtGZscSZDZQGlNExnFNaR24uf9f9/uo6S6kYExodw+W26a+YqFYxPYmV/J4vTOtVnc1rwe3T/+zg6ICaVf7xAOl9XxY0YpZ43sc9x2i83Ok98fYNGKTP1vYGwoT185jpGJvnOTTAghhP+SdHfRc2galGbAhufhncvhn/3h9QWw5j/HAvT40XDavXD9Yn19+aWvwJifSYDeRRuyHanujll0p/EpUQyMCaXeYuOrnV1v2dQRX2zPx2LTGJUUwdA+7QeBN502gFlDYmm02rnn3W00WGxuHZunOPujj/Vyf/QTtVyX3pmU9y2HjzYX3mqrJ7rwjvMcKe8bD5VTWNnQoddomsbW5sruUe4amksppZp7pK84IeU9t7yOy55fx7PL9QD9iknJLLl7hgToQgghXEaCdOHf6itgz+ew+F54cgw8MwG+fgAOfAOWWgiN1Yu+XfQ8/PoA3L4G5j0CA04Ho+/MOPorZ39053p0J6VUcwE3d1d5/8hR1f3SdmbRnQwGxb9+NpaYsAD2FVbzj6/3uXVsnpKep69HT/OB/ugnmjrgWCu2jrDY7PzO0RP90gl9m1u5Cd+QFBXMxH690DS9ZkBHFFQ2UFTViNGgGONjN5LaM3uovqZ8+b5jrdg+357Puf9dzbacCsKDTDx71Xj+cckYQgIkMVEIIYTryP8qwjOK98L6Rfrab3MImIMdHyFtfHY8Dgg59pwpGDQ7HNmmp7BnLIP8zfpzTsYASJkKg+bCoDMgfhQY5F6UO1Q3WNiVrweHJ86kg74+/F/f7WdDdjm55XUkR7u+BdH+wmp25VdhNirOT0vq0GtiwwP518/GcsOrm3ht7SFmpsZwxvB4l4/NUzRNa26/5osB0NRBvWGpPpPekXXpL67OYn9RNdGhAfz+3K71RBfutWBMApsPH2XJjiP8fMaAk+7vTHUfnhBOcID/ZEVMHdibILOBwqoGtuYc5d2NuXzkuOk4oV8v/ntFGn17SWs1IYQQridBunC/pjp472ooz+z+sZQRtBNSlGOGHAvK+58GAaHdP484qc2Hj2LXoF/vEBIif1qtOTEqmOmDevNjRhmfbM3n3jNTXT4GZ2/0OUPjiA4N6PDrZg+N4+czBvDymmx+89EOvrl3JnERQSd/oQ/KKa+jos5CgNHAsATfW2M/tm8UQWYDZbVNHCyuabcOQE5ZHf/9Xu+J/vtzh9OrE79T4TnnjkngkSV72JZT0aEbcM1F45L9a1lRkNnIaYNiWLavmCtf2ECTzY5BwV1zU7ln7uBWi1QKIYQQriBBunC/ZX/RA/TwBJh4E1jqwFLf4nP98c81nbDdWn/sWJpNb4M2cLYelA+aA1EpXvvWTmXN/dEH/HQW3emS8X31IH1bHvecMdilFY+tNjufbmu9N3pHPHD2UNZllrGnoIpffZDOGzdNxmDwv4rMzlT34QnhBJp8b5YywGRgYr9o1mSUsj6rrM0gXdM0Hv58F41WO9MH9ebi8R3LjBCeFxcexNSBvVmbWcaSHQUnLey3tUVld38ze1gcy/YV02SzkxAZxJOXpzFloCzBEEII4V4SpAv3yl4FG57TH5//jF5FvbPsdrA2OAL2BgjvAwbfC0ZONSf2R2/N2aP68IfPdnG4rI7Nh48yqX/bAX1nrc4opaS6kV4h5uYCT50RaDLy1JXjWPj0GtZklPLi6ixuneXaKuK55XUcrWtyaxp6c9E4Hy7INXXgsSD9umn9W93ni/QjrDpQQoDJwN8uHCUtrHzcwrGJrM0sY3H6kXaD9EarjV1H9DaN4/2ksntL541O4O31hxkSH84jF4wkKkSyO4QQQrif5GoJ92mshs/v1B9PuKFrATroa8oDQiC0N0QmSYDuA2obrexsZz26U0iAiXNGJwCuLyDnPN4FaUkEmLr2p2xwXBh/WjgCgP/7dn9zK7PuaLLaWbLjCFe/tJ6Zjy/n/Gd+ZNWBkm4fty3OMftaZfeWnP3S12eVNxfgaqmyzsJfl+g90e+aM5iBsdIT3dedPbIPJoNiT0EVmSU1be63t6CaJqudXiFm+vX2v/Xb0aEBfHPf6Tx15TgJ0IUQQniMBOnCfb57GCpy9HT0+X/z9miEC205fBSbXSMpKvikhZOcvcu/3FFAfZNrWp5V1lv4bk/RccfvqssnJXPu6D5Y7Rr3vLuNmkZrl46TVVLDo1/tZdpjy7jrnW38mHGs5dgzyzO6Nca2WG325pslY32wsrvTmL5RBJuNlNc2caDopwHdP77ZS2lNE4Pjwrh11kAvjFB0Vq/QAGakxgCwJL3tKu/N69FTekl2hBBCCNFBEqQL9zj4PWx5TX98wSII9L2CVqLr2uqP3popA6JJigqmutHKd3sKXXL+JTuO0GS1MzQ+nFFJEd06llKKxy4aQ2JkEIfK6vjzF7s7/NoGi43Pt+dz+fPrmPvvlbywKouy2ibiIwK5e+5gPrptGmajYmN2efO6XFc6UFRDg8VOWKCJgTG+O/scYDIwsX/r/dI3HSrn3Y25ADx60WifXFcvWrfQ0TP9i/T8VjMkALY6Krv7S390IYQQwhdIkC5cr/4ofHG3/njKbTBgpnfHI1zOWTRuajvr0Z0MBsUljiJgH7ko5d2Z6n7JhCSXzM5Fhph58opxGJQ+xi/Sj7S7/8Giah5ZvIepjy3j3ve2syG7HIOCM4bF8eJ1E/nxt3P59fyhTOwfzQWO1nDPrXBBd4MTOFPdRydF+nzRu2Mp78eC9Car3hMd4IpJyUxupwih8D3zRsYTYDKQWVLLvsLqVvdpOZMuhBBCiI6RIF243tcPQvURiB4EZ/zJ26MRLlbfZGvuy92RmXSAix0p6T9mlFJY2dCt82eV1LA1pwKDggs72Bu9IyYPiOauuXqbuN9/spPc8rrjttc32fh4Sx6X/m8t8/6zild+zKaizkJiZBC/PHMIPz44l5dvmMS8EfHHtWa6zZG+vXRvERnFba/d7Qrn78GXi8Y5TXVcKxuyy7Hb9VnXF1ZlcrC4hpiwAB48Z5g3hye6ICLIzJyhsQAsbuXGVnF1A3lH61HKt5djCCGEEL5GgnThWnuXwI73QBngouf0gm+iR9mWcxSLTSMhMoiUk/RHduofE8rEfr2wazS3TeuqT7bqrz99SKzLe5vfM3cwE/r1orrRyr3vbcNqs7O3oIo/fb6LyY9+z68/TGfz4aMYDYr5I+J59cZJrP7tXO49M7XVXvEAg+PCOXN4PJoGL67Kcul403P19ehpfhAAjU5qsS69uJpDpbU89YO+Vv8PC0ZIUS4/tXCsnvK+eMeRn6S8b3ekug+JCyc8yOzpoQkhhBB+S4J04Tq1pbDkPv3x9HsgebJXhyPcY332sf7onUk1v9TRy/zjrXltrl89GbtdO9YbvZsF41pjMhp48vI0woNMbM2pYNb/reCc/67m9XWHqW6w0rdXML85ayjrHpzLC9dNZM7QOIwdSDO/fbY+m/7ptnyKqrqXSeBU32Rjf5GeYuzOFm+u0nJd+rrMMn7/2U6arHZmpsZwviPQE/5n7rA4gs1Gcsvr2ZFXedy2bY72gP7YH10IIYTwJgnShWtoGnz5K6gtgdjhMOd33h6RcJPm/ugDT74evaVzxyQQaDKQUVzzkzfznTl3fkU94UEm5o2I79IxTiY5OoRHLxoNQH5FPSaD4tzRfXjz55NZ9Zs53DlncKdn8Cf0i2ZS/1402ey8sibbJePcfaQSm10jNjyQhEjXZhS4i3Nd+rPLM/gxo4xA6Ynu90ICTJzp+Ld4Ysr71sPO9ehRnh6WEEII4dckSBeusetj2PM5GEx6mrsp0NsjEm7QYLGx3TE7NqWTRb4igsycNbIPoM+md8VHjtctGJNIkNl9VcAXjk3kXz8by8PnDWfdQ2ew6OoJzEyN7VZxtttmDQLg7Q05VNZbuj3GdMeNjrF9I/0myHUG6aU1TQDcc0Yq/XqHenNIwgUWjkkAYMmOguZ6A1abvflm3HgpGieEEEJ0igTpovuqC+HLX+uPT/8NJKZ5dTjCfbbnVtBktRMbHsiAmM4HV5c4Ut6/SD9Co7VzPdNrGq18vVNv4eZMnXenSyf05RczBxIb7pobTnOGxjEkPoyaRitvbzjc7eOlO26WjPWDVHenMX0jCQnQb64MiQ/j5pnSE70nmDU0lvAgE4VVDWx2zJ7vL6qm3mIjPNDEoFjfbQ8ohBBC+CIJ0kX3aBosvhcaKiBhLMz8tbdHJNzI2Xqts+vRnWYMjiE+IpCKOgvL9xV36rVf7yyg3mJjQEwo4/0wfdZgUNx6uj6b/sqaQzRYOneT4kQ7/Kiyu5PZaGDBmARCAow8dvEYAkzyX1BPEGgyNmfJLNmhp7xvcxSNS0uJ8vn2gEIIIYSvkXdIonu2vw0HvgFjAFz4HBilgq8nNVptPLH0QPOsqrttyO7aenQno0Fx4Thnz/TOVXl3pshfMt41vdG94fy0RBIjgyitaWyuUt8VFXVNHCrTW8SN6ev7ld1b+uclY9jy8Dwm9JMU6J5kgSPl/audBVhtdrY6+6P70U0kIYQQwldIkC66riIXvnlIfzzndxA/wrvjOQW9tzGXp5Yd5K53t2Kzd61iekc1WY+98Z7Wwf7orbnUUZV9xf5iymoaO/Sa3PI61meVoxRc5Iaq7p5iNhr4uSPF+4VVmV3+nTnX+vbvHeJ3rcuUUgQHuK+egPCO0wbH0CvETGlNE+uzypvbr42TmzFCCCFEp0mQLrrGbocv7oLGKug7SW+5JjzOWU05t7yelQc6lz7eWTvyKmiw2IkJC+jWGtPU+HDG9I3Eatf4fPuRk7+AY73Vpw3sTVJU6/3I/cUVk5KJDDZzqKyOb3cXdukYzswJf2i9Jk4NZqOBc0brs+lvrDtEVmktAGlyjQohhBCdJkG66JrNL0PWCjAF62nuBpkZ87QjFfXNRZoA3ljX/WJk7dng6I8+uYvr0Vty9jjvSJV3TdP4pDnV3X9n0Z1CA01cP60fAM+tzOxSz/h0P1yPLnq+hWP0fvff7SkCYGBMKL1C/SvTQwghhPAFEqSLzivPgqV/1B+f+WeIGezV4ZyqvtxRAOhvhJWClQdKOOSYvXKH5v7oA7q2Hr2l88cmYjYqdh+pYl9hVbv7bjl8lENldYQEGDl7VJ9un9sXXDe9P4EmAzvyKlmXWdap12qaxvZcPd09Ldm/1qOLnm3ygGjiWnRDSPPDAo9CCCGEL5AgXXSO3Qaf3QGWOug/Eybf4u0RnbIWO6oo33haf2YNiUXT4K317plNt9jsbHHM2k/pxnp0p16hAcwdFgfAx1van03/yLH93NEJhAaaun1uXxATFshlE5MBeG5VVqdeW1DZQGlNI0aDYkSCBOnCdxgNinMdKe8A46Q/uhBCCNElEqSLzln/P8hZBwFhcMGzYJBLyBsOl9WyI68Sg4JzRidw/bT+AHywOZf6pu619mrNzvxK6ppsRIWYGRIX7pJjOlPXP912BKvN3uo+DRZbc8ZAT0h1b+nmmQMxKFh1oITdRyo7/Dpn67Wh8eFSgE34nIVjE5sf+2OrRCGEEMIXSIQlOq5kPyx7RH981t+hVz/vjucUtsQRuE4fFENMWCCzhsSSEh1CVYOVL9K73tqrLc7+6JP7R7us5/HsoXFEhwZQWtPIqoMlre7z7e5CqhutJEUFM2VA92fwfUlK7xDOc6zhfX5lx2fTnanuYyXVXfig8SlRnD2yD3OHxTGsT4S3hyOEEEL4JQnSRcfYrPDpbWBrhMFnwvjrvT2iLtE0jfc25nS5qravcFZ1XzhWTy01GBTXTE0B4PW1h7tUjKw93e2P3poAk4EL0vQg9eM2eqZ/7Oglfsn4JJfdHPAlt56ut2NbsuMIueV1HXqNs7L7WKmaLXyQUornrp3AKzdMwtgD/80KIYQQniBBuuiYH/8DR7ZCUCSc/zR0s7q3t7y8JpsHP9nJHW9vpaiqwdvD6ZKM4mr2FVZjNirOGnmskNplE5MJNBnYU1DV3M/cFaw2O5sP6ceb6oL16C05U9iX7imiss5y3LaiqgbWOGbYL+5hqe5Oo5IimZkag12DF1effDbdbtfYma/PpEv7NSGEEEKInkmCdHFyhTthxT/1x+c8DhGJ7e/vo5bvL+bRr/YCYLNrzQXJ/M3idD3VfWZqLFEhx9obRYUENM9Mu7Id256CKmoarUQEmVyevjoyMYJhfcJpstmbC+E5fbotH7sGE/v1on9MqEvP60tunzUI0OsJlNU0trtvVmkNNY1WgswGhsR3vVe9EEIIIYTwXRKki7bVlMCyv8Jr54HdAsMWwJjLvT2qLskoruaed7Zh12BwnB7cvLcpB7vdtWnh7qZpWnMw60x1b+k6RwG5r3YWUFLdfsDXUc3r0QdEuzx9VSnVas90TdOaq75fMqFnzqI7TRvUmzF9I2mw2Hl97aF29013rEcfnRSJySh/voUQQggheiJ5lyd+qjwbvvw1PDkKVv8LGiohbgQs+I9fprlX1DXx89c3U91oZXL/aD6+fTrhQSZyy+tZl9W5HtXetregmqySWgJMBs4cHv+T7aOSIhmfEoXFpq+9dwVX9kdvzQXjEjEaFNtyKsgsqQFgR14lB4trCDQZOG/MT29G9CRKKW5zzKa/vu4wtY3WNvdNd1R2l1R3IYQQQoieS4J0cUzBDvjoJnh6PGx6CawNkDgeLnsDblsDYXHeHmGnWWx27nxnK4fL6kiKCuZ/14wnMtjMhWlJALzrokDWU5yz6HOHxhEeZG51H+ds+tsbctpsbdZRNrvGxkP6TLor+qO3Ji48iNNTYwD4xDGb7pxVP2tkHyLa+D57krNG9mFATCiV9Rbe25Tb5n7NReOSozwzMCGEEEII4XESpJ/qNA2yVsKbF8HzM2HXx6DZYdAZcP1iuPkHGHEBGPyzH/Nfl+zhx4wyQgOMvHzDRHqHBQJw+aRkAL7bXUR5bZM3h9hhmqaxxBGkL2gl1d3pnNF96B0aQGFVA0v3FHXrnHsLqqhusBIWaGJEgvvaKTlT2j/dmk+DxcYXjur1PT3V3cloUNw8U6/0/vLqLCyt3FxptNrYW1ANwNi+0n5NCCGEEKKnkiD9VGW3we7P4MU58Mb5kPkDKAOMugRuXQXXfgIDTvfL9HanN9cf5o11h1EK/nN52nFFz0YlRTI6KZImm7159tbXpedVklteT0iAkbnD2s5qCDQZuXKy3o6tuwXkNmTrs+gT+/dy6xroM4fHExFk4khlA49+tZeKOgvxEYHMGBzjtnP6movHJxETFsiRyga+2H7kJ9v3FVTTZLMTFWImJTrECyMUQgghhBCeIEH6qcbSAFteg2cmwYfXw5FtYAqCSb+Au7fCpa9Awlhvj7Lb1maW8ucvdgNw//yhzG/Rqszpisn6bPq7G3Nc3lfcHZY4ZpfPGB5PSICp3X2vmpKCQcG6rDIOFlV3+Zwb3Lwe3SnIbGTB2OMr0184LumU6rMcZDZy04z+ADy/KvMnRQ13ONajj+0bhfLjm2dCCCGEEKJ9EqSfKhoqYc1/4L9jYPG9UJ4JQVFw+m/gvl1w3r8heoC3R+kSh8tquePtrdjsGhekJXLH7EGt7nf+2ESCzUYyS2rZfNh1fcXdwW7XWLJDb722sAOF1BKjgpk3Qi8s19XZdHuL9eiu7o/emktO6IV+aQ/tjd6eq6f0IyzQxIGiGlYcKD5u23ZHZXdJdRdCCCGE6NkkSO/pqgth6R/hP6Pg+z9DTRGEJ8JZj8Ivd8HchyEs1tujdJnqBgs/f30zFXUWxiZH8c9LxrQ56xgeZG5uY/bexraLdfmCLTlHKaxqIDzQxKyhHft9Xe8oIPfJ1jyqGyydPueB4moq6iyEBBgZleT+wHB8ShQDHP3Qx/SNJDU+3O3n9DWRwWaunqIvVXhuRdZx25yV3aVonBBCCCFEzyZBek929DAsmgo//hcaqyBmKFywCO5Nh2l3QmDPCoJsdo173t1GRnEN8RGBvHjtBILM7Re8u8KxdvvLnUeorO98IOspix2p7vNH9iHQ1LEiftMG9WZwXBi1TTY+3Zbf6XM6+6NP6NcLswd6ciuluN3RiszZkuxUdNOMAZiNio2HytniyPCobrA0t6eT9mtCCCGEED2bBOk9ld0On90O9Uchdhhc8S7csR7GXQ2mAG+Pzi0e/2Yfy/eXEGgy8OJ1E4mLCDrpa8YlRzEkPowGi50vtnc+kPUEq83OVzv1VPf2qrqfSCnFtVP7AXrKe2fX3Tv7o08d6N716C1dNimZjL+fw7mje3Zv9PbERwRx0Ti9ReBzKzMB2JlfiaZBUlQwseGB3hyeEEIIIYRwMwnSe6r1i+Dwj2AOhSvfhWHngqHn/ro/2pLH86v09OB//Wxsh2cblVJcMUmfTX93Y65PFpDbkF1OaU0TUSHmTlc7v3h8EqEBRjKKa1iXWdbh12maxkZHZfcpA9y/Hr0ld1aR9xe3nD4IpWDpniIyiqvZkedYj54s69GFEEIIIXo6eTfcExXvg2WP6I/P+jtED/TueNxsy+FyfvfJTgDumTuYhY4q4R118fgkAkwG9hRUsTO/0h1D7BZnb/RzRvXpdNp5eJCZix0F2F5fd6jDr8sorqGstokgs0HSq71gcFwY84brhf+eX5lFem4FIKnuQgghhBCnAgnSexqbBT69BWyNMHgeTLjB2yNyq/yKem59cwtNNjtnjYznvjOHdPoYUSEBnDNKb9H2ro8VkLPY7Hy9qxCAhWM6d/PB6dppesr70j1FHKmo79Br1jtm0cen9CLAJH8mvOE2R1eCz7bnNy89GCtBuhBCCCFEjyfvvnuaVf+CgnS9vdr5T0MP7qdc12Tl5tc3U1rTxPCECJ64LA1DF/tqO1Pev9ieT22j1ZXD7JY1GaVU1FmICQtkShfXhg+JD2fawN7YNXhnQ06HXuOp/uiibeNTejF5QDQWm8bROgtKwWhpvyaEEEII0eNJkN6T5G+BVf+nPz7v3xDRc4tv2e0av/4gnT0FVcSEBfDidRMIDTR1+XhTB0bTv3cItU02vnT0I/cFzqru543ug7GLNyAArnPMpr+7MYdGq63dfTVNY0O25/qji7bd3qLK/eDYMMK6cY0LIYQQQgj/IEF6T2Gph09vA80GIy+G0Zd6e0Ru9eSyg3y9q5AAo4Hnr51A314h3TqeUorLnQXkNnVsttndGiw2vttdBMCCTq6zP9G8EfH0iQiirLaJr3cWtrtvdmktJdWNBJgM0pPby2YPjWVYH71VovwuhBBCCCFODRKk9xTLHoHSAxDWR59F78GW7DjCU8sOAvD3i0YxoZ9rZnsvndAXk0GxLaeC/YXVLjlmd6w8UEJNo5WEyCAmpPTq1rFMRgNXT9FvQrxxkgJyzln0cclRJ+0zL9xLKcUjF4xibHJUczs9IYQQQgjRs0mQ3hNkr9JbroG+Dj2k56Yo78yr5P4P0wG4eeYAfjYx2WXHjg0P5ExHRe13N3p/Nv1YqntCl9fat3TF5BTMRsXWnAp2tVPF3lmkrKtr4IVrTR4Qzed3niYz6UIIIYQQpwgJ0v1dQxV8dof+eMINMGS+V4fjDpqmsa+wipdWZ/GLNzbRYLEze2gsD54z3OXnumKyHvR/ui2fBkv7a7fdqa7JyrK9xQCdbinXltjwQM4ZpdcpaGs2XdM0NmQ51qN7uD+6EEIIIYQQAqQKkb/75iGozIWofjD/b94ejcsUVTWw5mApazL0j5LqxuZtg+PCeOrKcd0qpNaWmamxJEUFk19Rz7e7C7kgLcnl5+iIZXuLqbfYSIkOYYwLK3pfN60fX6Qf4fPtR/jducOJCgk4bnvO0XoKqxowGxXjupliL4QQQgghhOg8CdL92b6vYPtbgIKLnoPAcG+PqMtqG61syC5j9cFS1hws5WBxzXHbg81GJg+IZmZqDJdO6EtEkNkt4zAaFD+b2Jcnvz/IuxtzvBakL9mhp7ovGJOAcmEbvQn9ejEiIYI9BVV8sDmXW04fdNz2jdlHAb0fd3CArEcXQgghhBDC0yRI91e1pbD4Hv3x9Luh33TvjqeTbHaNHXkVrDlYyuqMUrblHMVi05q3KwVjkiKZkRrDjMGxjO8XRaDJM0HjZROTeWrZQdZnlZNdWsuAmFCPnNepusHC8v0lACwY45pUdyelFNdN68eDn+zkrfU5/GLGwOPWu2865Gy9JuvRhRBCCCGE8AYJ0v2RpsHie6G2BGKHw5zft7lrk9WOyaBcUnisuw6X1bLqYClrDpawLrOMqgbrcduTo4OZMTiWmakxTB/U+yep2J6SGBXMrCGxLN9fwnubcnjIDWvf27N0TxFNVjuDYkMZnuD67IgL0pJ49Ku95JTXsfJACXOGxTVv23hIn0mfIv3RhRBCCCGE8AoJ0v3Rjvdh3xIwmODi58Ec1Opu2aW1XPHCOjQN7j0zlcsmJmM2er5W4K78Sv75zT5WHyw97vmIIBPTB8UwIzWGmakx9Ovt2Rnr9lwxOYXl+0v4eEsev543lACT535uzqruC8cmujTV3Sk4wMhlE5N5aU02r6871ByklzdCfkUDJoNiQj9Zjy6EEEIIIYQ3SJDubyrz4KsH9MezH4SEsa3udrS2iRtf3UhRlV5w7fef7uLl1dncf9ZQzhnVxy3B34kOldbyr+/2s2RHAUBz8DczNYYZqbGMTop0S/E3V5g7LI7Y8EBKqhtZtreIc0YneOS8FXVNzTczXJ3q3tI1U/vx0ppsVh4o4XBZLYkRAWRU6b+L0X0jCQmQPw1CCCGEEEJ4g7Rg8yd2O3x+JzRWQtJEOO2Xre7WaLVx65tbOFRWR1JUMA+dM4zeoQFkldZyx9tbufDZH1mbUdrqa12huKqB33+6kzOfWMmSHQUoBRemJfLDr2fz/q3TuGtuKmnJUT4boAOYjQYundAXgPc25XrsvN/sKsRq1xieEMHguDC3nad/TCizhsSiafDW+sMAZFTqv48pA2Q9uhBCCCGEEN4iQbo/2fwyZK0AU7Bezd3409lOTdN46OOdbDxUTnigiVdvnMStswax8oE53HtGKqEBRtLzKrnqpQ1c+/IGduVXumx4VQ0W/u/bfcz6vxW8vSEHq11j9tBYvrx7Jk9eMY6U3iEuO5cnXDFJ75m+6mAJeUfrPHJOZ9bBgjHun7m/fno/AN7flEt9k615Jl3WowshhBBCCOE9EqT7i9IM+O4P+uN5f4GY1FZ3e/qHDD7Zlo/RoHj26vEMidcLj4UFmvjlvCGsfGAON0zvj9moWH2wlAVPr+Hud7dxuKy2y0NrsNh4cVUWpz++nGeXZ1JvsTEuJYr3bpnKazdOZkRiRJeP7U39eocyfVBvNA0+2Jzn9vOVVDeyNlPPcFjoxlR3p1lD4kiODqaqwcpLaw5R1qgwKJgo69GFEEIIIYTwGgnS/YHNCp/eCtZ6GDALJt3c6m6fb8/niaUHAHjkgpGcPiT2J/vEhAXy5/NHsuxXs7kwLRGl9EJlZ/x7JX/8fBcl1Y0dH5Zd44PNucz91wr+/tVeKuosDI4L4/lrJ/DJ7dN7RBuvKyanAPDh5lxsdu0ke3fPN7sKsGswtm+kR7IOjAbFNVP02fRFK7MAGJkYQbibetALIYQQQgghTs7rQbpS6g6lVLZSqkEptUUpNbOdfWcrpbRWPoZ5cswe9+OTkL8ZAiPhwkVg+OmvbfOhcn7z4Q4Abp45gKsdwVdbUnqH8OQV41hy9wxmDYnFatd4Y91hZv3fcp74bj/VDZY2X6tpGt/tLuTsJ1fxwEc7OFLZQEJkEI9fMoZv7p3JWSM9U5jOE84aGU9UiJmCygZWHih267kWp+up7gvHun8W3emyickEmgxYHTcgJveXWXQhhBBCCCG8yatBulLqcuBJ4O/AOGA18LVSKuUkLx0KJLT4OOjGYXpXwQ5Y8Q/98Tn/hMi+P9nlcFktt7y5hSabnfkj4nmwE329RyZG8vpNk3n35qmMTY6irsnGUz9kMOv/VvDymmwarbbj9t+YXc6lz63jlje3cLC4hshgM787dxjL75/NZZOSMXmhxZs7BZqMXDxO/5m/u9F9BeQKKuvZdLgcgHM9VEkeoFdoAOe3uCkweYCsRxdCCCGEEMKbvB1R/Qp4WdO0lzRN26tp2n1ALnD7SV5XrGlaYYsP20n290/WRj3N3W6BYQtg7BU/2aWyzsKNr22ivLaJ0UmRPHlFWpeqpk8b1JvP7pjOc9eMZ2BsKOW1Tfx1yR7m/mslH2/JY/eRSm56bROXPb+OLYePEmQ2cMfsQax6YA63nD6IILPRFd+xT7pysl5A7od9xRRXNbjlHF/uKEDTYFL/XiRGBbvlHG25fnp/AAxoTEyJ8ui5hRBCCCGEEMfzWjNkpVQAMAH4xwmbvgOmn+Tl25RSQcAe4G+api1v5zyBQGCLp8IBLBYLFkvbKd3d4Txud49v+OGvGIv3oIXGYj37X2C1Hre9yWrn1je3kFVSS5+IQP531VjMSuvWec8YGsOswdF8vO0IT/+QSX5FPb/+ML15u9GguGxCEnfNGURcuP5jddfP0Vf0jw5ifEoUW3MqeH/jYW6bNdDl51icfgSAc0bGe/znOTQuhMcuGM7BvbsINvX836foGVz1d1YIT5DrVfgbuWaFP/GX67Uz41Oa5t5iWG2eWKlEIB84TdO0tS2e/x1wvaZpQ1t5zVDgdGALeuB9LXAbMFvTtFVtnOfPwJ9OfP6dd94hJMR3W4JF1+xnxsFHUWhsGHAvhVETjtuuafBupoENJQYCDRr3jrKRFOraMTTZYFWh4vt8A/U2xbjeds5NthPn2Ylen7ChWPFOppHegRoPj7PhyhbvZQ3wyDYTCo1HJtiICHDdsYUQQgghhBDeV1dXx1VXXQUQqWlaVXv7em0mvYUT7xKoVp7Td9S0/cD+Fk+tU0olA/cDrQbpwGPAEy2+Dgfy5s+fT0SEe1qDWSwWli5dyrx58zCbu1Yp27C5EDIM2EdfxviFf/jJ9udXZbOh5CAGBc9cPZ7ZrVRyd4ULgeoGKxX1TST38t2bGu42u8nKF4+voqzRSvSwKUwf5LrK9c+vygYOMnVgb664cKLLjtsZrrhmhfAkuWaFP5HrVfgbuWaFP/GX67Wqqt24/DjeDNJLARvQ54Tn44CiThxnPXBNWxs1TWsEmvuKOauOm81mt/8Su3WOabdCv8mo6IEYTjjGlzsK+NdSvVbenxaOZN5I91YDjzabiQ4/BafPW4g0m7kgLZG3N+Tw4dYjzBp24mXbdV/t0i/389OSvP6HxRP/LoRwJblmhT+R61X4G7lmhT/x9eu1M2PzWuE4TdOa0NPW552waR6w9qevaNM4oMBV4/IpieMgKPK4p7bmHOVXH2wH4Ibp/ZuLfgn3u9LRM/273UWU1za55JiZJTXsKajCZFCcPdJ1gb8QQgghhBDCP3m7uvsTwC+UUjcppYYrpf4DpADPASilHlNKveHcWSl1n1LqQqVUqlJqpFLqMeAS4BmvjN7DcsvruOWNzTRa7ZwxLI4/LBjh7SGdUkYlRTIqKYImm51Ptua55JhLHL3RZ6TG0CtUFqMLIYQQQghxqvNqkK5p2vvAfcAfge3oReHO1TTtsGOXBPSg3SkA+BewA72n+gzgPE3TPvHQkL2mqsHCTa9torSmiREJETx15bgutVoT3XPFJP1yfG9TLt0tuqhpGot36FXdF4xx75IFIYQQQgghhH/w9kw6mqYt0jStv6ZpgZqmTWhZpV3TtBs0TZvd4uvHNU0brGlasKZp0ZqmzdQ07SuvDNyDLDY7d769lYPFNcRHBPLyDRMJDfSFmn+nngvSEgk2G8kormHL4aNdPo7VZmdrzlEyimsIMBqYPzLehaMUQgghhBBC+CuJ9Hycpmn86YvdrD5YSrDZyMvXTyIh8tQu4uZN4UFmFoxJ4MMteby7MZeJ/aPRNI26JhvltU0//ahrorzG8bm2iaO1TZTVNlFZf6xP4qyhsUQE+W6RCyGEEEIIIYTnSJDu415anc07G3JQCp66chyjkiJP/iLhVldMTubDLXl8vj2ftZmllNU20WS1d+lY8RGB3DxzoItHKIQQQgghhPBXEqT7sG93F/Lo13sBePi8EcwbISnRvmB8Si9GJUWwK7+KgsqG5ucDTAZ6hwYQ3eKjV0gAvUMD6BX6089RwWZMRq+vOBFCCCGEEEL4EAnSfdSOvArufW8bmgbXTE3hptP6e3tIwkEpxRs3TWFnfiVRwebmgDwkwIhSUsxPCCGEEEII0XUSpPuojdnlNFjszBoSy58XjpTgz8dEhwYwa0ist4chhBBCCCGE6GEkSPdRv5g5kOToEKYP6i0p0UIIIYQQQghxipAg3YedNbKPt4cghBBCCCGEEMKDZIpWCCGEEEIIIYTwERKkCyGEEEIIIYQQPkKCdCGEEEIIIYQQwkdIkC6EEEIIIYQQQvgICdKFEEIIIYQQQggfIUG6EEIIIYQQQgjhIyRIF0IIIYQQQgghfIQE6UIIIYQQQgghhI+QIF0IIYQQQgghhPAREqQLIYQQQgghhBA+QoJ0IYQQQgghhBDCR0iQLoQQQgghhBBC+AgJ0oUQQgghhBBCCB8hQboQQgghhBBCCOEjJEgXQgghhBBCCCF8hATpQgghhBBCCCGEj5AgXQghhBBCCCGE8BEmbw/AW6qqqtx2bIvFQl1dHVVVVZjNZredRwhXkWtW+Bu5ZoU/ketV+Bu5ZoU/8ZfrtTPxp9I0zY1D8T1KqSQgz9vjEEIIIYQQQghxyumraVp+ezucikG6AhKBajeeJhz9RkBfN59HCFeRa1b4G7lmhT+R61X4G7lmhT/xp+s1HDiinSQIP+XS3R0/kHbvXHSXfh8AgGpN09yXVy+Ei8g1K/yNXLPCn8j1KvyNXLPCn/jZ9dqh8UnhOCGEEEIIIYQQwkdIkC6EEEIIIYQQQvgICdLdoxH4i+OzEP5Arlnhb+SaFf5Erlfhb+SaFf6kx12vp1zhOCGEEEIIIYQQwlfJTLoQQgghhBBCCOEjJEgXQgghhBBCCCF8hATpQgghhBBCCCGEj5AgXQghhBBCCCGE8BESpLuBUuoOpVS2UqpBKbVFKTXT22MSAkApdbpSarFS6ohSSlNKXXjCdqWU+rNje71SaoVSaqSXhitOcUqph5RSm5RS1UqpYqXUZ0qpoSfsI9es8AlKqduVUjuUUlWOj3VKqXNabJdrVfgsx99bTSn1ZIvn5JoVPsNxLWonfBS22N6jrlcJ0l1MKXU58CTwd2AcsBr4WimV4s1xCeEQCqQDd7Wx/QHgV47tk4BCYKlSKtwzwxPiOLOAZ4GpwDzABHynlAptsY9cs8JX5AEPAhMdHz8An7d4kyjXqvBJSqlJwC3AjhM2yTUrfM1uIKHFx+gW23rU9Sot2FxMKbUB2Kpp2u0tntsLfKZp2kPeG5kQx1NKacBFmqZ95vhaAUeAJzVN+6fjuUCgCPitpmnPe2usQgAopWKBYmCWpmmr5JoVvk4pVQ78BngFuVaFD1JKhQFbgTuAh4HtmqbdJ39fha9RSv0ZuFDTtLRWtvW461Vm0l1IKRUATAC+O2HTd8B0z49IiE4ZAPShxfWraVojsBK5foVviHR8Lnd8lmtW+CSllFEpdQV69tI65FoVvutZ4EtN074/4Xm5ZoUvSnWks2crpd5TSg10PN/jrleTtwfQw8QARvS7Ni0VoV84Qvgy5zXa2vXbz8NjEeI4jrvkTwBrNE3b5XharlnhU5RSo9GD8iCgBj1baY9SyvkmUa5V4TMcN5ImoC/POJH8fRW+ZgNwHXAAiEfP/FjrWFLU465XCdLd48Q1BKqV54TwVXL9Cl/0DDAGmNHKNrlmha/YD6QBUcAlwOtKqVkttsu1KnyCUioZ+C8wX9O0hnZ2lWtW+ARN075u8eVOpdQ6IBO4Hljv3O2El/nt9Srp7q5VCtj46ax5HD+9syOEr3FWyJTrV/gUpdTTwPnAHE3T8lpskmtW+BRN05o0TcvQNG2zow5NOnAvcq0K3zMB/frbopSyKqWs6MU673E8dl6Xcs0Kn6RpWi2wE0ilB/6NlSDdhTRNawK2oFchbmkesNbzIxKiU7LR/8g1X7+OOguzkOtXeIGjncozwMXAXE3Tsk/YRa5Z4esUEIhcq8L3LEOvjJ3W4mMz8LbjcRZyzQof5igMNxwooAf+jZV0d9d7AnhTKbUZfV3aLUAK8JxXRyUEzVVcB7d4aoBSKg0o1zQtx9Ef9XdKqYPAQeB3QB3wjqfHKgR6QaOrgAuAaqWU8w55paZp9ZqmaXLNCl+hlHoU+BrIBcKBK4DZwNlyrQpfo2laNbCr5XNKqVqgzFn3Q65Z4UuUUv8CFgM56DPkDwMRwOs98W+sBOkupmna+0qp3sAf0fv37QLO1TTtsHdHJgSgF4dZ3uLrJxyfXwduAB4HgoFFQC/0Ih3zHf+ZC+FpzlaWK054/kbgNcdjuWaFr4gH3kT/v78Svef02ZqmLXVsl2tV+Bu5ZoUv6Qu8i16ouwR9HfrUFjFWj7pepU+6EEIIIYQQQgjhI2RNuhBCCCGEEEII4SMkSBdCCCGEEEIIIXyEBOlCCCGEEEIIIYSPkCBdCCGEEEIIIYTwERKkCyGEEEIIIYQQPkKCdCGEEEIIIYQQwkdIkC6EEEIIIYQQQvgICdKFEEIIIYQQQggfIUG6EEIIIYQQQgjhIyRIF0IIIYQQQgghfIQE6UIIIYSbKKWilFJaKx8V3h6bEEIIIXyTBOlCCCGE+10CJDg+7vPuUIQQQgjhyyRIF0IIIdzH5PhcpmlaoaZphUBlazsqpV5rZcb9yRbbNaXUhS2+/kUr+xxSSt3XynE/a/H12UqpNUqpCqVUmVJqiVJqUHvfhFJqheNcF5/w/DbH87MdXxuVUi8rpbKVUvVKqf1KqXtbOd5NSqndSqlGpVSBUuqZFtuilFIvKKWKlFINSqldSqkFjm03nJiFoJRa7RhDmuPr2S1+fnalVLFjTEEtXvMrpdROpVStUipXKbVIKRXW3s9ACCGE8BQJ0oUQQgj3CXR8buzAvgr4hmMz7uva3FGpUOARoKYLYwoFngAmAWcAduBTpdTJ3hPkA7e0GMNkIPaEfQxAHnAZMMIxxkeVUpe1eN3twLPAC8Bo4Hwgw7HNAHwNTAeucRzjQcDW2oAcNw3S2hjvUCDJcZzLgRtbbLMD9wCjgOuBucDjbX/rQgghhOeYTr6LEEIIIboo2vG5ugP7moEax2w7SqmmdvZ9ANhDF/4f1zTt45ZfK6V+DhSjB8S72nnpF8AlSql+mqYdRg/YXwH+0OLYFuBPLV6TrZSajh60f+B47mHg35qm/bfFfpscn88EJgPDNU074Hguq7XBKKXMwD8dH39tZZdiTdMqHDc0moCjLcb55Alj/APwP+CONr53IYQQwmNkJl0IIYRwnyTH54IO7BsB1J5sJ6VUIvAr4P42dvmnUqrG+QFcfcLrByml3lFKZSmlqoBsx6aUk5y6CXgT+IVSKhy4CHi9lfHdppTarJQqcZz/ZuexlVJxQCKwrI1zpAF5LQL09tyJvnTg7Ta25ymlaoGD6LPz77cY4xyl1FKlVL5Sqhp4A+jtCOiFEEIIr5IgXQghhHCfEUCJpmnlHdg3ETjSgf3+Dnyoadr2Nrb/H3qw6/z44oTti4He6MHzFMcHQEAHzv0Cetr49cB3QFnLjY609v+gz7DPd5z/1RbHrj/J8U+23XmeXugz+L8GtDZ2mwmMRU/pnwD80fHafsBX6FkDlzi23el4jbkj5xdCCCHcSdLdhRBCCPc5A1h7sp0cM7jDgcdOsmsacCn6euu2lGqaltHi2NVAlONxb8d5btU0bbXjuRknG5+TpmkHlFIHgUeBC1vZZSawVtO0RS3O31yUTtO0aqXUIfSfy/JWXr8D6KuUGnKS2fQ/AKs1TVuplOrfxj7ZmqZVABlKqbfQ16X/BZiI/v7n15qm2R1jvKyNYwghhBAeJ0G6EEII4WJKqWDgKuAc4E6lVJ8WmyP1XVQfoARIRS9aVoGelt2e+9HXc3dkxr01R9Fnv29RShWgp6H/o5PH+C16ML4c/XtpKQO4Til1Fnoa/bXoBeqyW+zzZ+A5pVQx+vcbDpymadrTjqB7FfCxUupXjuMNAzRN075xvD4EfT38+JOMM85R0b0v8DNgn+P5TPT3P3crpRYDpwG3deL7F0IIIdxK0t2FEEII17sceAm9Yvsi9DXpzo8n0defFwDJ6EGrCThT07STVWuvRk9n7xLHzPEV6Cneu9BT03/TyWNs1DTt35qmtZZm/hzwCfr67w3oafWLTnj96+i94u8AdgNL0G9UOF2CXkjuXfTieI8DxhbbzcCrHVi3vh/9Z/yN4/FdjvNvR1/T/1v0n8HVwEMnOZYQQgjhMar1/2OFEEII0VVKqRuAGzRNm93OPhowQNO0Qx4alhBCCCH8gMykCyGEEK5XD5ysWFwRbfT/FkIIIcSpS2bShRBCCCGEEEIIHyEz6UIIIYQQQgghhI+QIF0IIYQQQgghhPAREqQLIYQQQgghhBA+QoJ0IYQQQgghhBDCR0iQLoQQQgghhBBC+AgJ0oUQQgghhBBCCB8hQboQQgghhBBCCOEjJEgXQgghhBBCCCF8xP8DZB9CKhxfZ/IAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def binary_Search(A, key):                                                # Алгоритм бинарного поиска\n",
    "    sorted_list=sorted(A)\n",
    "    low = 0\n",
    "    high = len(sorted_list) - 1\n",
    "\n",
    "    while low <= high:\n",
    "        mid = (low + high) // 2\n",
    "        guess = sorted_list[mid]\n",
    "        if guess == key:\n",
    "            return mid\n",
    "        if guess > key:\n",
    "            high = mid - 1\n",
    "        else:\n",
    "            low = mid + 1\n",
    "    return -1\n",
    "\n",
    "\n",
    "C = [random.randint(0,19 ) for i in range(20)]                             # создание массива случайных чисел\n",
    "key2 = 3 \n",
    "print(\"Массив :  \",C)\n",
    "print(\"Ключ к массиву :\",key2)\n",
    "\n",
    "res1 = linear_Search(C,  key2)                                             # поиск числа в массиве\n",
    "if(res1 == -1): \n",
    "    print(\"Элемент не найден\") \n",
    "else: \n",
    "    print(\"Индекс найденного элемента: \", res1) \n",
    "\n",
    "D = ''.join(random.choice(sample_str) for _ in range(20))                  # создание строки случайных символов\n",
    "key22 = 'z' \n",
    "print(\"Строка :  \",D)\n",
    "print(\"Ключ к строке :\",key22)\n",
    "\n",
    "res2 = linear_Search(D,  key22)                                            # поиск символа в строке\n",
    "if(res2 == -1): \n",
    "    print(\"Элемент не найден\") \n",
    "else: \n",
    "    print(\"Индекс найденного элемента: \", res2)   \n",
    "\n",
    "\n",
    "t2=np.zeros(50)                                                             # Создание массива для результатов обработки времени\n",
    "t22=np.zeros(50)\n",
    "n2=np.arange(1,51,1)                                                        # Создание массива длин вектора \n",
    "n=1\n",
    "while n<51:\n",
    "    C = [random.randint(0, 9) for i in range(n)]                            # Создание вектора размера n \n",
    "    t2[n-1] = timeit.timeit('binary_Search(C,key2)', globals=globals())     # Расчет времени выполнения алгоритма \n",
    "    D = ''.join(random.choice(sample_str) for _ in range(n))                # Создание вектора размера n \n",
    "    t22[n-1] = timeit.timeit('binary_Search(D,key22)', globals=globals())   # Расчет времени выполнения алгоритма \n",
    "    n+=1\n",
    "\n",
    "fig, ax = plt.subplots(figsize = [12,6],dpi = 100)                          # Построение графиков \n",
    "plt.grid(visible=True)\n",
    "ax.set_xlabel(\"Длина массива\") \n",
    "ax.set_ylabel(\"Время выполнения сек\") \n",
    "ax.set_title('Оценка времени выполнения алгоритма бинарного поиска ') \n",
    "ax.plot(n2,t2,n2,t22)\n",
    "ax.legend(labels = (\"поиск числав в массиве\",\"Поиск символа в строке\"), loc=\"upper left\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3)   Напишите   функцию   хеширования   для   массива,   каждый   элемент\n",
    "которого — строка. Можно сделать любой «простой» хеш (деление на простое\n",
    "число, полином, и т. п.)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def hash8(message, table,tab_size):                    # Алгоритм Пирсона\n",
    "    hash = len(message) % tab_size\n",
    "    for i in message:\n",
    "        hash = table[(hash+ord(i)) % tab_size]\n",
    "    return hash"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4) С помощью функции из п. 3 составьте хеш-таблицу для списка из не\n",
    "менее   чем   200   000   слов.   Проведите   статистический   анализ   получившейся\n",
    "таблицы:   сколько   ячеек   хеш-таблицы   оказалось   пустыми,   сколько   содержит\n",
    "только одно слово, сколько содержит только два слова и т. п."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "колличество пусттых ячеек : 24302\n",
      "колличество ячеек содержащих одно слово : 23822\n",
      "колличество ячеек содержащих два слова : 12031\n",
      "колличество ячеек содержащих три слова : 4141\n",
      "колличество ячеек содержащих четыре слова : 1012\n",
      "колличество ячеек содержащих пять слов : 188\n",
      "колличество ячеек содержащих шесть слов : 39\n",
      "колличество ячеек содержащих семь слов : 1\n"
     ]
    }
   ],
   "source": [
    "def insert(hash_table, value,tab_size):                                # Функция заполнения хэш-таблицы\n",
    "    hash_key = hash8(value,example_table,tab_size)\n",
    "    hash_table[hash_key].append(value) \n",
    "\n",
    "Sl=[[] for _ in range(2**16)]                                          # Создание словаря\n",
    "n=0  \n",
    "while n<2**16+1:  \n",
    "    Sl[n-1]= ''.join(random.choice(sample_str) for _ in range(10))                 \n",
    "    n+=1\n",
    "\n",
    "example_table = list(range(0, len(Sl)))                                # Создание таблицы для алгоритма Пирсона\n",
    "shuffle(example_table)\n",
    "\n",
    "     \n",
    "hash_table = [[] for _ in range(len(Sl))]                             # Заполнение хэш-таблицы\n",
    "n=0\n",
    "while n<len(Sl):\n",
    "    insert(hash_table,Sl[n],len(Sl))\n",
    "    n+=1\n",
    "\n",
    "\n",
    "nul=0\n",
    "one=0\n",
    "two=0\n",
    "three=0\n",
    "four=0\n",
    "five=0\n",
    "six=0\n",
    "seven=0  \n",
    "for i in range(len(hash_table)):\n",
    "    if len(hash_table[i])==0:\n",
    "       nul+=1\n",
    "    elif len(hash_table[i])==1:\n",
    "        one+=1\n",
    "    elif len(hash_table[i])==2:\n",
    "        two+=1\n",
    "    elif len(hash_table[i])==3:\n",
    "        three+=1\n",
    "    elif len(hash_table[i])==4:\n",
    "        four+=1  \n",
    "    elif len(hash_table[i])==5:\n",
    "        five+=1\n",
    "    elif len(hash_table[i])==6:\n",
    "        six+=1\n",
    "    elif len(hash_table[i])==7:\n",
    "        seven+=1              \n",
    "\n",
    "print(\"Количество пустых ячеек :\", nul)\n",
    "print(\"Количество ячеек содержащих одно слово :\",one)\n",
    "print(\"Количество ячеек содержащих два слова :\",two)\n",
    "print(\"Количество ячеек содержащих три слова :\",three)\n",
    "print(\"Количество ячеек содержащих четыре слова :\",four)\n",
    "print(\"Количество ячеек содержащих пять слов :\",five)\n",
    "print(\"Количество ячеек содержащих шесть слов :\",six)\n",
    "print(\"Количество ячеек содержащих семь слов :\",seven)\n",
    "     "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5) Повторите п. 5, используя встроенную питоновскую функцию hash."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "колличество пусттых ячеек : 24156\n",
      "колличество ячеек содержащих одно слово : 24070\n",
      "колличество ячеек содержащих два слова : 12020\n",
      "колличество ячеек содержащих три слова : 4010\n",
      "колличество ячеек содержащих четыре слова : 1039\n",
      "колличество ячеек содержащих пять слов : 209\n",
      "колличество ячеек содержащих шесть слов : 29\n",
      "колличество ячеек содержащих семь слов : 3\n"
     ]
    }
   ],
   "source": [
    "def bits(n):\n",
    "    return np.binary_repr(n,width=64)\n",
    "\n",
    "\n",
    "\n",
    "def insert1(hash_table, value):                                        # Функция заполнения хэш-таблицы\n",
    "    hash_key = int(bits(hash(value))[-16:],2)\n",
    "    hash_table[hash_key].append(value) \n",
    "\n",
    "Sl=[[] for _ in range(2**16)]                                          # Создание словаря\n",
    "n=0  \n",
    "while n<2**16+1:  \n",
    "    Sl[n-1]= ''.join(random.choice(sample_str) for _ in range(6))                 \n",
    "    n+=1\n",
    "\n",
    "   \n",
    "hash_table = [[] for _ in range(2**16)]                             # Заполнение хэш-таблицы\n",
    "n=0\n",
    "while n<2**16:\n",
    "    insert1(hash_table,Sl[n])\n",
    "    n+=1\n",
    "\n",
    "\n",
    "nul=0\n",
    "one=0\n",
    "two=0\n",
    "three=0\n",
    "four=0\n",
    "five=0\n",
    "six=0\n",
    "seven=0  \n",
    "for i in range(len(hash_table)):\n",
    "    if len(hash_table[i])==0:\n",
    "       nul+=1\n",
    "    elif len(hash_table[i])==1:\n",
    "        one+=1\n",
    "    elif len(hash_table[i])==2:\n",
    "        two+=1\n",
    "    elif len(hash_table[i])==3:\n",
    "        three+=1\n",
    "    elif len(hash_table[i])==4:\n",
    "        four+=1  \n",
    "    elif len(hash_table[i])==5:\n",
    "        five+=1\n",
    "    elif len(hash_table[i])==6:\n",
    "        six+=1\n",
    "    elif len(hash_table[i])==7:\n",
    "        seven+=1              \n",
    "\n",
    "print(\"Количество пустых ячеек :\", nul)\n",
    "print(\"Количество ячеек содержащих одно слово :\",one)\n",
    "print(\"Количество ячеек содержащих два слова :\",two)\n",
    "print(\"Количество ячеек содержащих три слова :\",three)\n",
    "print(\"Количество ячеек содержащих четыре слова :\",four)\n",
    "print(\"Количество ячеек содержащих пять слов :\",five)\n",
    "print(\"Количество ячеек содержащих шесть слов :\",six)\n",
    "print(\"Количество ячеек содержащих семь слов :\",seven)\n",
    "     "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6) Решите задачу в п. 4, используя питоновский словарь."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "колличество пусттых ячеек : 24179\n",
      "колличество ячеек содержащих одно слово : 24009\n",
      "колличество ячеек содержащих два слова : 12045\n",
      "колличество ячеек содержащих три слова : 4055\n",
      "колличество ячеек содержащих четыре слова : 1008\n",
      "колличество ячеек содержащих пять слов : 202\n",
      "колличество ячеек содержащих шесть слов : 36\n",
      "колличество ячеек содержащих семь слов : 2\n"
     ]
    }
   ],
   "source": [
    "def random_key():                                                                      # создание ключа\n",
    "    return ''.join(random.choice(sample_str) for _ in range(6))\n",
    "\n",
    "\n",
    "def random_value():                                                                    # создание значений \n",
    "    return random.choice([\n",
    "        lambda: random.randint(0, 100),\n",
    "    ])();\n",
    "    \n",
    "\n",
    "def random_dict():                                                                     # Создание словаря\n",
    "    return {random_key(): random_value() for _ in range(2**16)}\n",
    "\n",
    "def insert1(hash_table, value):                                                        # Функция заполнения хэш-таблицы\n",
    "    hash_key = int(bits(hash(value))[-16:],2)\n",
    "    hash_table[hash_key].append(value) \n",
    "\n",
    "D=random_dict()\n",
    "Dd=list(D.keys())\n",
    "   \n",
    "hash_table = [[] for _ in range(len(Dd))]                                                 # Заполнение хэш-таблицы\n",
    "n=0\n",
    "while n<len(Dd):\n",
    "    insert1(hash_table,Dd[n])\n",
    "    n+=1\n",
    "\n",
    "\n",
    "nul=0\n",
    "one=0\n",
    "two=0\n",
    "three=0\n",
    "four=0\n",
    "five=0\n",
    "six=0\n",
    "seven=0  \n",
    "for i in range(len(hash_table)):\n",
    "    if len(hash_table[i])==0:\n",
    "               nul+=1\n",
    "    elif len(hash_table[i])==1:\n",
    "        one+=1\n",
    "    elif len(hash_table[i])==2:\n",
    "        two+=1\n",
    "    elif len(hash_table[i])==3:\n",
    "        three+=1\n",
    "    elif len(hash_table[i])==4:\n",
    "        four+=1  \n",
    "    elif len(hash_table[i])==5:\n",
    "        five+=1\n",
    "    elif len(hash_table[i])==6:\n",
    "        six+=1\n",
    "    elif len(hash_table[i])==7:\n",
    "        seven+=1              \n",
    "\n",
    "print(\"Количество пустых ячеек :\", nul)\n",
    "print(\"Количество ячеек содержащих одно слово :\",one)\n",
    "print(\"Количество ячеек содержащих два слова :\",two)\n",
    "print(\"Количество ячеек содержащих три слова :\",three)\n",
    "print(\"Количество ячеек содержащих четыре слова :\",four)\n",
    "print(\"Количество ячеек содержащих пять слов :\",five)\n",
    "print(\"Количество ячеек содержащих шесть слов :\",six)\n",
    "print(\"Количество ячеек содержащих семь слов :\",seven)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7) Решите задачу в п. 6, используя функцию «идеального хеша». Функцию\n",
    "получить у преподавателя."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "колличество пусттых ячеек : 24008\n",
      "колличество ячеек содержащих одно слово : 24244\n",
      "колличество ячеек содержащих два слова : 12064\n",
      "колличество ячеек содержащих три слова : 4000\n",
      "колличество ячеек содержащих четыре слова : 979\n",
      "колличество ячеек содержащих пять слов : 200\n",
      "колличество ячеек содержащих шесть слов : 40\n",
      "колличество ячеек содержащих семь слов : 0\n"
     ]
    }
   ],
   "source": [
    "def random_key():                                                                      # создание ключа\n",
    "    return ''.join(random.choice(sample_str) for _ in range(6))\n",
    "\n",
    "\n",
    "def random_value():                                                                    # создание значений \n",
    "    return random.choice([\n",
    "        lambda: random.randint(0, 100),\n",
    "    ])();\n",
    "    \n",
    "\n",
    "def random_dict():                                                                     # Создание словаря\n",
    "    return {random_key(): random_value() for _ in range(2**16)}\n",
    "\n",
    "def insert1(hash_table, value):                                                        # Функция заполнения хэш-таблицы\n",
    "    hash_key = int(bits(hash(value))[-16:],2)\n",
    "    hash_table[hash_key].append(value) \n",
    "\n",
    "D=random_dict()\n",
    "Dd=list(D.keys())\n",
    "   \n",
    "hash_table = [[] for _ in range(len(Dd))]                                                 # Заполнение хэш-таблицы\n",
    "n=0\n",
    "while n<len(Dd):\n",
    "    insert1(hash_table,Dd[n])\n",
    "    n+=1\n",
    "\n",
    "\n",
    "nul=0\n",
    "one=0\n",
    "two=0\n",
    "three=0\n",
    "four=0\n",
    "five=0\n",
    "six=0\n",
    "seven=0  \n",
    "for i in range(len(hash_table)):\n",
    "    if len(hash_table[i])==0:\n",
    "               nul+=1\n",
    "    elif len(hash_table[i])==1:\n",
    "        one+=1\n",
    "    elif len(hash_table[i])==2:\n",
    "        two+=1\n",
    "    elif len(hash_table[i])==3:\n",
    "        three+=1\n",
    "    elif len(hash_table[i])==4:\n",
    "        four+=1  \n",
    "    elif len(hash_table[i])==5:\n",
    "        five+=1\n",
    "    elif len(hash_table[i])==6:\n",
    "        six+=1\n",
    "    elif len(hash_table[i])==7:\n",
    "        seven+=1              \n",
    "\n",
    "print(\"Количество пустых ячеек :\", nul)\n",
    "print(\"Количество ячеек содержащих одно слово :\",one)\n",
    "print(\"Количество ячеек содержащих два слова :\",two)\n",
    "print(\"Количество ячеек содержащих три слова :\",three)\n",
    "print(\"Количество ячеек содержащих четыре слова :\",four)\n",
    "print(\"Количество ячеек содержащих пять слов :\",five)\n",
    "print(\"Количество ячеек содержащих шесть слов :\",six)\n",
    "print(\"Количество ячеек содержащих семь слов :\",seven)"
   ]
  }
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